Joseph Yuan-Chieh Lo

Journal Article ArXiv · September 24, 2024 IMPORTANCE: Clinical imaging trials are crucial for definitive evaluation of medical innovations, but the process is inefficient, expensive, and ethically-constrained. Virtual imaging trial (VIT) approach address these limitations by emulating the componen ... Link to item Cite

Improving Computer-aided Detection for Digital Breast Tomosynthesis by Incorporating Temporal Change.

Journal Article Radiol Artif Intell · September 2024 Purpose To develop a deep learning algorithm that uses temporal information to improve the performance of a previously published framework of cancer lesion detection for digital breast tomosynthesis. Materials and Methods This retrospective study analyzed ... Full text Link to item Cite

Evolutionary Measures Show that Recurrence of DCIS is Distinct from Progression to Breast Cancer.

Preprint · August 16, 2024 Full text Link to item Cite

Patient Characteristics Impact Performance of AI Algorithm in Interpreting Negative Screening Digital Breast Tomosynthesis Studies.

Journal Article Radiology · May 2024 Featured Publication Background Artificial intelligence (AI) is increasingly used to manage radiologists' workloads. The impact of patient characteristics on AI performance has not been well studied. Purpose To understand the impact of patient characteristics (race and ethnici ... Full text Link to item Cite

A Method for Efficient De-identification of DICOM Metadata and Burned-in Pixel Text.

Journal Article J Imaging Inform Med · April 8, 2024 De-identification of DICOM images is an essential component of medical image research. While many established methods exist for the safe removal of protected health information (PHI) in DICOM metadata, approaches for the removal of PHI "burned-in" to image ... Full text Link to item Cite

Application of deep learning on mammographies to discriminate between low and high-risk DCIS for patient participation in active surveillance trials.

Journal Article Cancer Imaging · April 5, 2024 BACKGROUND: Ductal Carcinoma In Situ (DCIS) can progress to invasive breast cancer, but most DCIS lesions never will. Therefore, four clinical trials (COMET, LORIS, LORETTA, AND LORD) test whether active surveillance for women with low-risk Ductal carcinom ... Full text Link to item Cite

AsymMirai: Interpretable Mammography-based Deep Learning Model for 1-5-year Breast Cancer Risk Prediction.

Journal Article Radiology · March 2024 Featured Publication Background Mirai, a state-of-the-art deep learning-based algorithm for predicting short-term breast cancer risk, outperforms standard clinical risk models. However, Mirai is a black box, risking overreliance on the algorithm and incorrect diagnoses. Purpos ... Full text Link to item Cite

Abstract A038: Evaluating DCIS progression: A comparative analysis of CNA predictive power derived from lpWGS and WES data

Conference Cancer Research · February 1, 2024 AbstractDuctal carcinoma in situ (DCIS) is a very common non-life threatening, pre-invasive form of breast cancer constituting 25% of all new breast cancer diagnoses in the USA, and is normally treated with ... Full text Cite

Classification performance bias between training and test sets in a limited mammography dataset.

Journal Article PLoS One · 2024 OBJECTIVES: To assess the performance bias caused by sampling data into training and test sets in a mammography radiomics study. METHODS: Mammograms from 700 women were used to study upstaging of ductal carcinoma in situ. The dataset was repeatedly shuffle ... Full text Link to item Cite

A Residual-Attention Multimodal Fusion Network (ResAMF-Net) for Detection and Classification of Breast Cancer

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2024 Digital breast tomosynthesis (DBT), synthetic mammography, and full-field digital mammography (FFDM) are commonly used medical imaging modalities for breast cancer screening. Due to the data complexity, most CAD research applies to only one modality, which ... Full text Cite

Virtual NLST: Towards Replicating National Lung Screening Trial

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2024 Virtual Imaging Trials, known as VITs, provide a computational substitute for clinical trials. These traditional trials tend to be sluggish, costly, and frequently deficient in definitive evidence, all the while subjecting participants to ionizing radiatio ... Full text Cite

Random Walk Small Intestine Models for Virtual Patient Populations

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2024 We develop the XCAT series of phantoms for medical imaging research. The phantoms model different individuals over various ages, heights, and weights, but a current drawback is they do not include small intestine variability. Each phantom has a small intes ... Full text Cite

Ipsilateral Lesion Detection Refinement for Tomosynthesis.

Journal Article IEEE Trans Med Imaging · October 2023 Featured Publication Computer-aided detection (CAD) frameworks for breast cancer screening have been researched for several decades. Early adoption of deep-learning models in CAD frameworks has shown greatly improved detection performance compared to traditional CAD on single- ... Full text Link to item Cite

Utility of a Rule-Based Algorithm in the Assessment of Standardized Reporting in PI-RADS.

Journal Article Acad Radiol · June 2023 RATIONALE AND OBJECTIVES: Adoption of the Prostate Imaging Reporting & Data System (PI-RADS) has been shown to increase detection of clinically significant prostate cancer on prostate mpMRI. We propose that a rule-based algorithm based on Regular Expressio ... Full text Link to item Cite

Classification performance bias between training and test sets in a limited mammography dataset.

Journal Article medRxiv · February 23, 2023 OBJECTIVES: To assess the performance bias caused by sampling data into training and test sets in a mammography radiomics study. METHODS: Mammograms from 700 women were used to study upstaging of ductal carcinoma in situ. The dataset was repeatedly shuffle ... Full text Link to item Cite

Multi-view DBT Grid-Attention Detection Framework

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2023 Most of the existing CAD frameworks for digital breast tomosynthesis (DBT) are single-view only, while radiologists typically utilize information from multiple screening views to better detect breast cancer lesions. Previously, we developed the Retina-Matc ... Full text Cite

Automatic quality control in computed tomography volumes segmentation using a small set of XCAT as reference images

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2023 Deep learning methods have performed superiorly to segment organs of interest from Computed Tomography images than traditional methods. However, the trained models do not generalize well at the inference phase, and manual validation and correction are not ... Full text Cite

A user interface to communicate interpretable AI decisions to radiologists

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2023 Tools for computer-aided diagnosis based on deep learning have become increasingly important in the medical field. Such tools can be useful, but require effective communication of their decision-making process in order to safely and meaningfully guide clin ... Full text Cite

Anomaly Detection of Calcifications in Mammography Based on 11,000 Negative Cases.

Journal Article IEEE Trans Biomed Eng · May 2022 In mammography, calcifications are one of the most common signs of breast cancer. Detection of such lesions is an active area of research for computer-aided diagnosis and machine learning algorithms. Due to limited numbers of positive cases, many supervise ... Full text Link to item Cite

Multi-label annotation of text reports from computed tomography of the chest, abdomen, and pelvis using deep learning.

Journal Article BMC Med Inform Decis Mak · April 15, 2022 BACKGROUND: There is progress to be made in building artificially intelligent systems to detect abnormalities that are not only accurate but can handle the true breadth of findings that radiologists encounter in body (chest, abdomen, and pelvis) computed t ... Full text Open Access Link to item Cite

Virtual Lung Screening Trial (VLST): An In Silico Replica of the National Lung Screening Trial for Lung Cancer Detection.

Improving Computer-aided Detection for Digital Breast Tomosynthesis by Incorporating Temporal Change.

Evolutionary Measures Show that Recurrence of DCIS is Distinct from Progression to Breast Cancer.

Preprint · August 16, 2024 Full text Link to item Cite

Patient Characteristics Impact Performance of AI Algorithm in Interpreting Negative Screening Digital Breast Tomosynthesis Studies.

A Method for Efficient De-identification of DICOM Metadata and Burned-in Pixel Text.

Application of deep learning on mammographies to discriminate between low and high-risk DCIS for patient participation in active surveillance trials.

AsymMirai: Interpretable Mammography-based Deep Learning Model for 1-5-year Breast Cancer Risk Prediction.

Abstract A038: Evaluating DCIS progression: A comparative analysis of CNA predictive power derived from lpWGS and WES data

Classification performance bias between training and test sets in a limited mammography dataset.

A Residual-Attention Multimodal Fusion Network (ResAMF-Net) for Detection and Classification of Breast Cancer

Virtual NLST: Towards Replicating National Lung Screening Trial

Random Walk Small Intestine Models for Virtual Patient Populations

Ipsilateral Lesion Detection Refinement for Tomosynthesis.

Utility of a Rule-Based Algorithm in the Assessment of Standardized Reporting in PI-RADS.

Classification performance bias between training and test sets in a limited mammography dataset.

Multi-view DBT Grid-Attention Detection Framework

Automatic quality control in computed tomography volumes segmentation using a small set of XCAT as reference images

A user interface to communicate interpretable AI decisions to radiologists

Anomaly Detection of Calcifications in Mammography Based on 11,000 Negative Cases.

Multi-label annotation of text reports from computed tomography of the chest, abdomen, and pelvis using deep learning.

Prediction of Upstaging in Ductal Carcinoma in Situ Based on Mammographic Radiomic Features.

Journal Article Radiology · April 2022 Background Improving diagnosis of ductal carcinoma in situ (DCIS) before surgery is important in choosing optimal patient management strategies. However, patients may harbor occult invasive disease not detected until definitive surgery. Purpose To assess t ... Full text Link to item Cite

Technical note: Controlling the attenuation of 3D-printed physical phantoms for computed tomography with a single material.

Journal Article Med Phys · April 2022 PURPOSE: The purpose of this work was to characterize and improve the ability of fused filament fabrication to create anthropomorphic physical phantoms for CT research. Specifically, we sought to develop the ability to create multiple levels of X-ray atten ... Full text Link to item Cite

Classification of Multiple Diseases on Body CT Scans Using Weakly Supervised Deep Learning.

Journal Article Radiol Artif Intell · January 2022 Featured Publication PURPOSE: To design multidisease classifiers for body CT scans for three different organ systems using automatically extracted labels from radiology text reports. MATERIALS AND METHODS: This retrospective study included a total of 12 092 patients (mean age, ... Full text Link to item Cite

Corrections to "iPhantom: A Framework for Automated Creation of Individualized Computational Phantoms and its Application to CT Organ Dosimetry".

Journal Article IEEE J Biomed Health Inform · January 2022 In [1], the dose estimation accuracy using the alternative baseline method under modulated tube current was not correctly calculated due to an unintentional simulation error. ... Full text Link to item Cite

Quality or quantity: toward a unified approach for multi-organ segmentation in body CT

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2022 Organ segmentation of medical images is a key step in virtual imaging trials. However, organ segmentation datasets are limited in in terms of quality (because labels cover only a few organs) and quantity (since case numbers are limited). In this study, we ... Full text Cite

Virtual versus reality: external validation of COVID-19 classifiers using XCAT phantoms for chest radiography

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2022 Many published studies use deep learning models to predict COVID-19 from chest x-ray (CXR) images, often reporting high performances. However, the models do not generalize well on independent external testing. Common limitations include the lack of medical ... Full text Cite

Interpretable Deep Learning Models for Better Clinician-AI Communication in Clinical Mammography

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2022 There is increasing interest in using deep learning and computer vision to help guide clinical decisions, such as whether to order a biopsy based on a mammogram. Existing networks are typically black box, unable to explain how they make their predictions. ... Full text Cite

Virtual vs. reality: External validation of COVID-19 classifiers using XCAT phantoms for chest computed tomography

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2022 Research studies of artificial intelligence models in medical imaging have been hampered by poor generalization. This problem has been especially concerning over the last year with numerous applications of deep learning for COVID-19 diagnosis. Virtual imag ... Full text Cite

Co-occurring diseases heavily influence the performance of weakly supervised learning models for classification of chest CT

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2022 Despite the potential of weakly supervised learning to automatically annotate massive amounts of data, little is known about its limitations for use in computer-aided diagnosis (CAD). For CT specifically, interpreting the performance of CAD algorithms can ... Full text Cite

A case-based interpretable deep learning model for classification of mass lesions in digital mammography

Journal Article Nature Machine Intelligence · December 1, 2021 Interpretability in machine learning models is important in high-stakes decisions such as whether to order a biopsy based on a mammographic exam. Mammography poses important challenges that are not present in other computer vision tasks: datasets are small ... Full text Cite

A new method to accurately identify single nucleotide variants using small FFPE breast samples.

Journal Article Brief Bioinform · November 5, 2021 Most tissue collections of neoplasms are composed of formalin-fixed and paraffin-embedded (FFPE) excised tumor samples used for routine diagnostics. DNA sequencing is becoming increasingly important in cancer research and clinical management; however it is ... Full text Link to item Cite

A Data Set and Deep Learning Algorithm for the Detection of Masses and Architectural Distortions in Digital Breast Tomosynthesis Images.

Journal Article JAMA Netw Open · August 2, 2021 IMPORTANCE: Breast cancer screening is among the most common radiological tasks, with more than 39 million examinations performed each year. While it has been among the most studied medical imaging applications of artificial intelligence, the development a ... Full text Link to item Cite

iPhantom: A Framework for Automated Creation of Individualized Computational Phantoms and Its Application to CT Organ Dosimetry.

Journal Article IEEE J Biomed Health Inform · August 2021 OBJECTIVE: This study aims to develop and validate a novel framework, iPhantom, for automated creation of patient-specific phantoms or "digital-twins (DT)" using patient medical images. The framework is applied to assess radiation dose to radiosensitive or ... Full text Link to item Cite

Multimodal Patient-Specific Registration for Breast Imaging Using Biomechanical Modeling with Reference to AI Evaluation of Breast Tumor Change.

Journal Article Life (Basel) · July 26, 2021 BACKGROUND: The strategy to combat the problem associated with large deformations in the breast due to the difference in the medical imaging of patient posture plays a vital role in multimodal medical image registration with artificial intelligence (AI) in ... Full text Link to item Cite

Mixed-Methods Study to Predict Upstaging of DCIS to Invasive Disease on Mammography.

Journal Article AJR Am J Roentgenol · April 2021 BACKGROUND. The incidence of ductal carcinoma in situ (DCIS) has steadily increased, as have concerns regarding overtreatment. Active surveillance is a novel treatment strategy that avoids surgical excision, but identifying patients with occult invasive di ... Full text Link to item Cite

IAIA-BL: A Case-based Interpretable Deep Learning Model for Classification of Mass Lesions in Digital Mammography

Journal Article · March 23, 2021 Interpretability in machine learning models is important in high-stakes decisions, such as whether to order a biopsy based on a mammographic exam. Mammography poses important challenges that are not present in other computer vision tasks: datasets are smal ... Link to item Cite

Assessment of task-based performance from five clinical DBT systems using an anthropomorphic breast phantom.

Journal Article Med Phys · March 2021 PURPOSE: Digital breast tomosynthesis (DBT) is a limited-angle tomographic breast imaging modality that can be used for breast cancer screening in conjunction with full-field digital mammography (FFDM) or synthetic mammography (SM). Currently, there are fi ... Full text Link to item Cite

Multi-Label Annotation of Chest Abdomen Pelvis Computed Tomography Text Reports Using Deep Learning

Journal Article · February 4, 2021 Featured Publication Purpose: To develop high throughput multi-label annotators for body (chest, abdomen, and pelvis) Computed Tomography (CT) reports that can be applied across a variety of abnormalities, organs, and disease states. Approach: We used a dictionary approach t ... Link to item Cite

Machine-learning-based multiple abnormality prediction with large-scale chest computed tomography volumes.

Journal Article Med Image Anal · January 2021 Featured Publication Machine learning models for radiology benefit from large-scale data sets with high quality labels for abnormalities. We curated and analyzed a chest computed tomography (CT) data set of 36,316 volumes from 19,993 unique patients. This is the largest multip ... Full text Link to item Cite

Machine-learning-based multiple abnormality prediction with large-scale chest computed tomography volumes.

Journal Article Medical Image Anal. · 2021 Full text Cite

IPhantom: An automated framework in generating personalized computational phantoms for organ-based radiation dosimetry

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2021 We propose an automated framework to generate 3D detailed person-specific computational phantoms directly from patient medical images. We investigate the feasibility of this framework in terms of accurately generating patient-specific phantoms and the clin ... Full text Cite

Retina-Match: Ipsilateral Mammography Lesion Matching in a Single Shot Detection Pipeline

Conference Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) · January 1, 2021 In mammography and tomosynthesis, radiologists use the geometric relationship of the four standard screening views to detect breast abnormalities. To date, computer aided detection methods focus on formulations based only on a single view. Recent multi-vie ... Full text Cite

Detection of masses and architectural distortions in digital breast tomosynthesis: a publicly available dataset of 5,060 patients and a deep learning model

Journal Article JAMA Netw Open. 2021;4(8):e2119100 · November 13, 2020 Breast cancer screening is one of the most common radiological tasks with over 39 million exams performed each year. While breast cancer screening has been one of the most studied medical imaging applications of artificial intelligence, the development and ... Link to item Cite

Predicting Upstaging of DCIS to Invasive Disease: Radiologists's Predictive Performance.

Journal Article Acad Radiol · November 2020 RATIONALE AND OBJECTIVES: The purpose of this study is to quantify breast radiologists' performance at predicting occult invasive disease when ductal carcinoma in situ (DCIS) presents as calcifications on mammography and to identify imaging and histopathol ... Full text Link to item Cite

Impact of Using Uniform Attenuation Coefficients for Heterogeneously Dense Breasts in a Dedicated Breast PET/X-ray Scanner.

Journal Article IEEE Trans Radiat Plasma Med Sci · September 2020 We investigated PET image quantification when using a uniform attenuation coefficient (μ) for attenuation correction (AC) of anthropomorphic density phantoms derived from high-resolution breast CT scans. A breast PET system was modeled with perfect data co ... Full text Link to item Cite

iPhantom: a framework for automated creation of individualized computational phantoms and its application to CT organ dosimetry

Journal Article · August 19, 2020 Objective: This study aims to develop and validate a novel framework, iPhantom, for automated creation of patient-specific phantoms or digital-twins (DT) using patient medical images. The framework is applied to assess radiation dose to radiosensitive orga ... Link to item Cite

Virtual clinical trials in medical imaging: a review.

Journal Article J Med Imaging (Bellingham) · July 2020 The accelerating complexity and variety of medical imaging devices and methods have outpaced the ability to evaluate and optimize their design and clinical use. This is a significant and increasing challenge for both scientific investigations and clinical ... Full text Link to item Cite

Prediction of Upstaged Ductal Carcinoma In Situ Using Forced Labeling and Domain Adaptation.

Journal Article IEEE Trans Biomed Eng · June 2020 OBJECTIVE: The goal of this study is to use adjunctive classes to improve a predictive model whose performance is limited by the common problems of small numbers of primary cases, high feature dimensionality, and poor class separability. Specifically, our ... Full text Link to item Cite

Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms.

Journal Article JAMA Netw Open · March 2, 2020 IMPORTANCE: Mammography screening currently relies on subjective human interpretation. Artificial intelligence (AI) advances could be used to increase mammography screening accuracy by reducing missed cancers and false positives. OBJECTIVE: To evaluate whe ... Full text Link to item Cite

Microcalcification localization and cluster detection using unsupervised convolutional autoencoders and structural similarity index

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2020 Detecting microcalcification clusters in mammograms is important to the diagnosis of breast diseases. Previous studies which mainly focused on supervised methods require abundant annotated training data but these data are usually hard to acquire. In this w ... Full text Cite

A multitask deep learning method in simultaneously predicting occult invasive disease in ductal carcinoma in-situ and segmenting microcalcifications in mammography

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2020 We proposed a two-branch multitask learning convolutional neural network to solve two different but related tasks at the same time. Our main task is to predict occult invasive disease in biopsy proven Ductal Carcinoma in-situ (DCIS), with an auxiliary task ... Full text Cite

Weakly supervised 3D classification of chest CT using aggregated multi-resolution deep segmentation features

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2020 Weakly supervised disease classification of CT imaging suffers from poor localization owing to case-level annotations, where even a positive scan can hold hundreds to thousands of negative slices along multiple planes. Furthermore, although deep learning s ... Full text Cite

Attention-guided classification of abnormalities in semi-structured computed tomography reports

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2020 Lack of annotated data is a major challenge to machine learning algorithms, particularly in the field of radiology. Algorithms that can efficiently extract labels in a fast and precise manner are in high demand. Weak supervision is a compromise solution, p ... Full text Cite

Assessment of task-based performance from five clinical DBT systems using an anthropomorphic breast phantom

Conference Proceedings of SPIE - The International Society for Optical Engineering · January 1, 2020 Purpose: There are currently five FDA approved commercial digital breast tomosynthesis (DBT) systems, all of which have varying geometry and exposure techniques. The aim of this work was to determine if an anthropomorphic breast phantom could be used to sy ... Full text Cite

Virtual imaging trials: An emerging experimental paradigm in imaging research and practice

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2020 As medical imaging technologies continue to accelerate in complexity, application, and multiplicity of design choices and use features, they should ideally be evaluated and optimized through human clinical trials. However, such trials are often impossible ... Full text Cite

Evaluation of possible phantoms for assessment of image quality in synthetic mammograms

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2020 Aim: Investigate 3D structured DBT phantoms with lesion models for use in the evaluation of synthetic mammography (SM) imaging performance. Methods: 4 phantoms were investigated: CDMAM, L1, CIRS BR3D and Modular DBT Phantom (two different inserts). The pha ... Full text Cite

CT phantom with 3D anthropomorphic, contrast-enhanced texture

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2020 Physical phantoms with realistic anatomical texture and composition (including contrast media) are of high value and relevance in evaluating the performance of clinical computed tomography (CT) imaging systems. They can offer assessments of image quality i ... Full text Cite

A four-alternative forced choice (4AFC) methodology for evaluating microcalcification detection in clinical full-field digital mammography (FFDM) and digital breast tomosynthesis (DBT) systems using an inkjet-printed anthropomorphic phantom.

Journal Article Med Phys · September 2019 PURPOSE: The advent of three-dimensional breast imaging systems such as digital breast tomosynthesis (DBT) has great promise for improving the detection and diagnosis of breast cancer. With these new technologies comes an essential need for testing methods ... Full text Link to item Cite

Mask Embedding in conditional GAN for Guided Synthesis of High Resolution Images

Journal Article · July 2, 2019 Recent advancements in conditional Generative Adversarial Networks (cGANs) have shown promises in label guided image synthesis. Semantic masks, such as sketches and label maps, are another intuitive and effective form of guidance in image synthesis. Direct ... Link to item Cite

Growth Dynamics of Mammographic Calcifications: Differentiating Ductal Carcinoma in Situ from Benign Breast Disease.

Journal Article Radiology · July 2019 Background Most ductal carcinoma in situ (DCIS) lesions are first detected on screening mammograms as calcifications. However, false-positive biopsy rates for calcifications range from 30% to 87%. Improved methods to differentiate benign from malignant cal ... Full text Link to item Cite

Can Digital Breast Tomosynthesis Replace Full-Field Digital Mammography? A Multireader, Multicase Study of Wide-Angle Tomosynthesis.

Journal Article AJR Am J Roentgenol · June 2019 OBJECTIVE. The purpose of this study was to test the hypothesis whether two-view wide-angle digital breast tomosynthesis (DBT) can replace full-field digital mammography (FFDM) for breast cancer detection. SUBJECTS AND METHODS. In a multireader multicase s ... Full text Link to item Cite

Three-dimensionally-printed anthropomorphic physical phantom for mammography and digital breast tomosynthesis with custom materials, lesions, and uniform quality control region.

Journal Article J Med Imaging (Bellingham) · April 2019 Anthropomorphic breast phantoms mimic patient anatomy in order to evaluate clinical mammography and digital breast tomosynthesis system performance. Our goal is to create a modular phantom with an anthropomorphic region to allow for improved lesion and cal ... Full text Link to item Cite

Special Section Guest Editorial: Special Section on 3D Printing in Medical Imaging

Journal Article Journal of Medical Imaging · April 1, 2019 Full text Cite

Multi-organ segmentation in clinical-computed tomography for patient-specific image quality and dose metrology

Conference Medical Imaging 2019: Physics of Medical Imaging · 2019 Cite

Synthesis and texture manipulation of screening mammograms using conditional generative adversarial network

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2019 Annotated data availability has always been a major limiting f actor for the development of algorithms in the field of computer aided diagnosis. The purpose of this study is to investigate the feasibility of using a conditional generative adversarial netwo ... Full text Cite

Malignant microcalcification clusters detection using unsupervised deep autoencoders

Journal Article Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2019 Detection and localization of microcalcification (MC) clusters are very important in mammography diagnosis. Supervised MC detectors require learning from extracted individual MCs and MC clusters. However, they are limited by number of datasets given that M ... Full text Cite

Multiview mammographic mass detection based on a single shot detection system

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2019 Detection of suspicious breast cancer lesion in screening mammography images is an important step for the downstream diagnosis the of breast cancer. A trained radiologist can usually take advantage of multi-view correlation of suspicious lesions to locate ... Full text Cite

Combining deep learning methods and human knowledge to identify abnormalities in computed tomography (CT) reports

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2019 Many researchers in the field of machine learning have addressed the problem of detecting anomalies within Computed Tomography (CT) scans. Training these machine learning algorithms requires a dataset of CT scans with identified anomalies (labels), usually ... Full text Cite

2.5D CNN model for detecting lung disease using weak supervision

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2019 Our goal is to develop a 2.5D CNN model to detect multiple diseases in multiple organs in CT scans. In this study we investigated detection of 4 common diseases in the lungs, which are atelectasis, edema, pneumonia and nodule. Most existing algorithms for ... Full text Cite

Classifying abnormalities in computed tomography radiology reports with rule-based and natural language processing models

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2019 Purpose: When conducting machine learning algorithms on classification and detection of abnormalities for medical imaging, many researchers are faced with the problem that it is hard to get enough labeled data. This is especially difficult for modalities s ... Full text Cite

Classification of chest CT using case-level weak supervision

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2019 Our goal is to investigate using only case-level labels extracted automatically from radiology reports to construct a multi-disease classifier for CT scans with deep learning method. We chose four lung diseases as a start: atelectasis, pulmonary edema, nod ... Full text Cite

Using inkjet 3D printing to create contrast-enhanced textured physical phantoms for CT

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2019 Anthropomorphic phantoms can serve as anatomically structured tools for assessing clinical computed tomography (CT) imaging systems. The aim of this project is to create highly customized 3D inkjet-printed, contrast-enhanced physical liver phantoms for use ... Full text Cite

Deep learning of 3D computed tomography (CT) images for organ segmentation using 2D multi-channel SegNet model

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2019 Purpose To accurately segment organs from 3D CT image volumes using a 2D, multi-channel SegNet model consisting of a deep Convolutional Neural Network (CNN) encoder-decoder architecture. Method We trained a SegNet model on the extended cardiac-Torso (XCAT) ... Full text Cite

Controlling the position-dependent contrast of 3D printed physical phantoms with a single material

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2019 Custom 3D printed physical phantoms are desired for testing the limits of medical imaging, and for providing patientspecific information. This work focuses on the development of low-cost, open source fused filament fabrication for printing of physical phan ... Full text Cite

Mask Embedding for Realistic High-Resolution Medical Image Synthesis

Conference Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) · January 1, 2019 Generative Adversarial Networks (GANs) have found applications in natural image synthesis and begin to show promises generating synthetic medical images. In many cases, the ability to perform controlled image synthesis using masked priors such as shape and ... Full text Cite

Prediction of Occult Invasive Disease in Ductal Carcinoma in Situ Using Deep Learning Features.

Journal Article J Am Coll Radiol · March 2018 PURPOSE: The aim of this study was to determine whether deep features extracted from digital mammograms using a pretrained deep convolutional neural network are prognostic of occult invasive disease for patients with ductal carcinoma in situ (DCIS) on core ... Full text Link to item Cite

Prediction of occult invasive disease in ductal carcinoma in situ using deep learning features

Conference CANCER RESEARCH · February 1, 2018 Link to item Cite

Virtual assessment of stereoscopic viewing of digital breast tomosynthesis projection images.

Journal Article J Med Imaging (Bellingham) · January 2018 Digital breast tomosynthesis (DBT) acquires a series of projection images from different angles as an x-ray source rotates around the breast. Such imaging geometry lends DBT naturally to stereoscopic viewing as two projection images with a reasonable separ ... Full text Link to item Cite

Learning better deep features for the prediction of occult invasive disease in ductal carcinoma in situ through transfer learning

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2018 Purpose: To determine whether domain transfer learning can improve the performance of deep features extracted from digital mammograms using a pre-trained deep convolutional neural network (CNN) in the prediction of occult invasive disease for patients with ... Full text Cite

Improving classification with forced labeling of other related classes: Application to prediction of upstaged ductal carcinoma in situ using mammographic features

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2018 Predicting whether ductal carcinoma in situ (DCIS) identified at core biopsy contains occult invasive disease is an import task since these "upstaged" cases will affect further treatment planning. Therefore, a prediction model that better classifies pure D ... Full text Cite

Anomaly detection for medical images based on a one-class classification

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2018 Detecting an anomaly such as a malignant tumor or a nodule from medical images including mammogram, CT or PET images is still an ongoing research problem drawing a lot of attention with applications in medical diagnosis. A conventional way to address this ... Full text Cite

3D printed anthropomorphic physical phantom for mammography and DBT with high contrast custom materials, lesions, and uniform chest wall region

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2018 Anthropomorphic breast phantoms mimic anatomy to evaluate the performance of clinical mammography and digital breast tomosynthesis (DBT) systems. Our goal is to make a phantom that mimics clinically relevant appearance of a patient to allow for improved im ... Full text Cite

Methodology for the objective assessment of lesion detection performance with breast tomosynthesis and digital mammography using a physical anthropomorphic phantom

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2018 Realistic breast phantoms serve as important tools when evaluating full field digital mammography (FFDM) and digital breast tomosynthesis (DBT) system modifications. Current breast phantoms contain either unrealistic features or uniform backgrounds. The pu ... Full text Cite

Evaluation of statistical breast phantoms with higher resolution

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2018 In previous work, we generated computational breast phantoms by using a principal component analysis (PCA) or "Eigenbreast" technique. For this study, we sought to address resolution limitations in the previous synthesized breast phantoms by analyzing new ... Full text Cite

Method for task-based evaluation of clinical FFDM and DBT systems using an anthropomorphic breast phantom

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2018 Because breast phantoms are central for evaluating 2D and 3D breast imaging systems, it is important to develop anthropomorphic, realistic phantoms that can be used in task-based assessment. The current phantoms available for use with full field digital ma ... Full text Cite

Synthetic breast phantoms from patient based eigenbreasts.

Journal Article Med Phys · December 2017 PURPOSE: The limited number of 3D patient-based breast phantoms available could be augmented by synthetic breast phantoms in order to facilitate virtual clinical trials (VCTs) using model observers for breast imaging optimization and evaluation. METHODS: T ... Full text Link to item Cite

Can Occult Invasive Disease in Ductal Carcinoma In Situ Be Predicted Using Computer-extracted Mammographic Features?

Journal Article Acad Radiol · September 2017 RATIONALE AND OBJECTIVES: This study aimed to determine whether mammographic features assessed by radiologists and using computer algorithms are prognostic of occult invasive disease for patients showing ductal carcinoma in situ (DCIS) only in core biopsy. ... Full text Link to item Cite

A novel physical anthropomorphic breast phantom for 2D and 3D x-ray imaging.

Journal Article Med Phys · February 2017 PURPOSE: Physical phantoms are central to the evaluation of 2D and 3D breast-imaging systems. Currently, available physical phantoms have limitations including unrealistic uniform background structure, large expense, or excessive fabrication time. The purp ... Full text Link to item Cite

Third generation anthropomorphic physical phantom for mammography and DBT: Incorporating voxelized 3D printing and uniform chest wall QC region

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2017 Physical breast phantoms provide a standard method to test, optimize, and develop clinical mammography systems, including new digital breast tomosynthesis (DBT) systems. In previous work, we produced an anthropomorphic phantom based on 500x500x500 μm breas ... Full text Cite

Prediction of occult invasive disease in ductal carcinoma in situ using computer-extracted mammographic features

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2017 Predicting the risk of occult invasive disease in ductal carcinoma in situ (DCIS) is an important task to help address the overdiagnosis and overtreatment problems associated with breast cancer. In this work, we investigated the feasibility of using comput ... Full text Cite

Can upstaging of ductal carcinoma in situ be predicted at biopsy by histologic and mammographic features?

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2017 Reducing the overdiagnosis and overtreatment associated with ductal carcinoma in situ (DCIS) requires accurate prediction of the invasive potential at cancer screening. In this work, we investigated the utility of pre-operative histologic and mammographic ... Full text Cite

A physical breast phantom for 2D and 3D x-ray imaging made through inkjet printing

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2017 Physical breast phantoms are used for imaging evaluation studies with 2D and 3D breast x-ray systems, serving as surrogates for human patients. However, there is a presently a limited selection of available phantoms that are realistic, in terms of containi ... Full text Cite

High-resolution, anthropomorphic, computational breast phantom: Fusion of rule-based structures with patient-based anatomy

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2017 While patient-based breast phantoms are realistic, they are limited by low resolution due to the image acquisition and segmentation process. The purpose of this study is to restore the high frequency components for the patient-based phantoms by adding powe ... Full text Cite

Detectability of artificial lesions in anthropomorphic virtual breast phantoms of variable glandular fraction

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2017 This work seeks to utilize a cohort of computational, patient-based breast phantoms and anthropomorphic lesions inserted therein to determine trends in breast lesion detectability as a function of several clinically relevant variables. One of the measures ... Full text Cite

Lesion detectability in stereoscopically viewed digital breast tomosynthesis projection images: A model observer study with anthropomorphic computational breast phantoms

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2017 Stereoscopic views of 3D breast imaging data may better reveal the 3D structures of breasts, and potentially improve the detection of breast lesions. The imaging geometry of digital breast tomosynthesis (DBT) lends itself naturally to stereo viewing becaus ... Full text Cite

Comparison of effects of dose on image quality in digital breast tomosynthesis across multiple vendors

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2017 In traditional radiography and computed tomography (CT), contrast is an important measure of image quality that, in theory, does not vary with dose. While increasing dose may increase the overall contrast-to-noise ratio (CNR), the contrast in an image shou ... Full text Cite

New applications of super-resolution in medical imaging

Chapter · January 1, 2017 The image processing algorithms collectively known as super-resolution have proven effective in producing high-quality imagery from a collection of low-resolution photographic images. In this chapter, we examine some of the advantages and challenges of app ... Full text Cite

Assessing task performance in FFDM, DBT, and synthetic mammography using uniform and anthropomorphic physical phantoms.

Journal Article Med Phys · October 2016 PURPOSE: The purpose of this study is to quantify the differences in detectability between full field digital mammography (FFDM), digital breast tomosynthesis (DBT), and synthetic mammography (SM) for challenging, low contrast signals, in the context of bo ... Full text Link to item Cite

Predicting false negative errors in digital breast tomosynthesis among radiology trainees using a computer vision-based approach

Journal Article Expert Systems with Applications · September 1, 2016 Purpose Digital breast tomosynthesis (DBT) can improve lesion visibility in comparison to mammography by eliminating breast tissue superimposition. While the benefits of DBT in breast cancer screening rely on well trained radiologists, the optimal training ... Full text Cite

Impact of breast structure on lesion detection in breast tomosynthesis, a simulation study.

Journal Article J Med Imaging (Bellingham) · July 2016 This study aims to characterize the effect of background tissue density and heterogeneity on the detection of irregular masses in breast tomosynthesis, while demonstrating the capability of the sophisticated tools that can be used in the design, implementa ... Full text Link to item Cite

Finite-element modeling of compression and gravity on a population of breast phantoms for multimodality imaging simulation.

Journal Article Med Phys · May 2016 PURPOSE: The authors are developing a series of computational breast phantoms based on breast CT data for imaging research. In this work, the authors develop a program that will allow a user to alter the phantoms to simulate the effect of gravity and compr ... Full text Link to item Cite

A quantitative metrology for performance characterization of five breast tomosynthesis systems based on an anthropomorphic phantom.

Journal Article Med Phys · April 2016 PURPOSE: In medical imaging systems, proper rendition of anatomy is essential in discerning normal tissue from disease. Currently, digital breast tomosynthesis (DBT) systems are evaluated using subjective evaluation of lesion visibility in uniform phantoms ... Full text Link to item Cite

Radiology Trainee Performance in Digital Breast Tomosynthesis: Relationship Between Difficulty and Error-Making Patterns.

Journal Article J Am Coll Radiol · February 2016 PURPOSE: The aim of this study was to better understand the relationship between digital breast tomosynthesis (DBT) difficulty and radiology trainee performance. METHODS: Twenty-seven radiology residents and fellows and three expert breast imagers reviewed ... Full text Link to item Cite

Population of 224 realistic human subject-based computational breast phantoms.

Journal Article Med Phys · January 2016 PURPOSE: To create a database of highly realistic and anatomically variable 3D virtual breast phantoms based on dedicated breast computed tomography (bCT) data. METHODS: A tissue classification and segmentation algorithm was used to create realistic and de ... Full text Link to item Cite

Identification of error making patterns in lesion detection on digital breast tomosynthesis using computer-extracted image features

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2016 Digital breast tomosynthesis (DBT) can improve lesion visibility by eliminating the issue of overlapping breast tissue present in mammography. However, this new modality likely requires new approaches to training. The issue of training in DBT is not well e ... Full text Cite

Design, fabrication, and implementation of voxel-based 3D printed textured phantoms for task-based image quality assessment in CT

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2016 In x-ray computed tomography (CT), task-based image quality studies are typically performed using uniform background phantoms with low-contrast signals. Such studies may have limited clinical relevancy for modern non-linear CT systems due to possible influ ... Full text Cite

Second generation anthropomorphic physical phantom for mammography and DBT: Incorporating voxelized 3D printing and inkjet printing of iodinated lesion inserts

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2016 Physical phantoms are needed for the evaluation and optimization of new digital breast tomosynthesis (DBT) systems. Previously, we developed an anthropomorphic phantom based on human subject breast CT data and fabricated using commercial 3D printing. We no ... Full text Cite

Eigenbreasts for statistical breast phantoms

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2016 To facilitate rigorous virtual clinical trials using model observers for breast imaging optimization and evaluation, we demonstrated a method of defining statistical models, based on 177 sets of breast CT patient data, in order to generate tens of thousand ... Full text Cite

Comparison of model and human observer performance in FFDM, DBT, and synthetic mammography

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2016 Reader studies are important in assessing breast imaging systems. The purpose of this work was to assess task-based performance of full field digital mammography (FFDM), digital breast tomosynthesis (DBT), and synthetic mammography (SM) using different pha ... Full text Cite

Investigation of optimal parameters for penalized maximum-likelihood reconstruction applied to iodinated contrast-enhanced breast CT

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2016 Although digital mammography has reduced breast cancer mortality by approximately 30%, sensitivity and specificity are still far from perfect. In particular, the performance of mammography is especially limited for women with dense breast tissue. Two out o ... Full text Cite

Semiautomated head-and-neck IMRT planning using dose warping and scaling to robustly adapt plans in a knowledge database containing potentially suboptimal plans.

Journal Article Med Phys · August 2015 PURPOSE: Prior work by the authors and other groups has studied the creation of automated intensity modulated radiotherapy (IMRT) plans of equivalent quality to those in a patient database of manually created clinical plans; those database plans provided g ... Full text Link to item Cite

Development of realistic physical breast phantoms matched to virtual breast phantoms based on human subject data.

Journal Article Med Phys · July 2015 PURPOSE: Physical phantoms are essential for the development, optimization, and evaluation of x-ray breast imaging systems. Recognizing the major effect of anatomy on image quality and clinical performance, such phantoms should ideally reflect the three-di ... Full text Link to item Cite

Does Breast Imaging Experience During Residency Translate Into Improved Initial Performance in Digital Breast Tomosynthesis?

Journal Article J Am Coll Radiol · July 2015 PURPOSE: To determine the initial digital breast tomosynthesis (DBT) performance of radiology trainees with varying degrees of breast imaging experience. METHODS: To test trainee performance with DBT, we performed a reader study, after obtaining IRB approv ... Full text Link to item Cite

Incorporating breast tomosynthesis into radiology residency: Does trainee experience in breast imaging translate into improved performance with this new modality?

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2015 Digital breast tomosynthesis (DBT) is a powerful new imaging modality that has the potential to transform breast cancer screening practices. The advantages over mammography include improved sensitivity and specificity as well as the detection of additional ... Full text Cite

The impact of breast structure on lesion detection in breast tomosynthesis

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2015 Virtual clinical trials (VCT) can be carefully designed to inform, orient, or potentially replace clinical trials. The focus of this study was to demonstrate the capability of the sophisticated tools that can be used in the design, implementation, and perf ... Full text Cite

A quantitative metrology for performance characterization of breast tomosynthesis systems based on an anthropomorphic phantom

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2015 Purpose: Common methods for assessing image quality of digital breast tomosynthesis (DBT) devices currently utilize simplified or otherwise unrealistic phantoms, which use inserts in a uniform background and gauge performance based on a subjective evaluati ... Full text Cite

Using computer-extracted image features for modeling of error-making patterns in detection of mammographic masses among radiology residents.

Journal Article Med Phys · September 2014 PURPOSE: Mammography is the most widely accepted and utilized screening modality for early breast cancer detection. Providing high quality mammography education to radiology trainees is essential, since excellent interpretation skills are needed to ensure ... Full text Link to item Cite

Radiation dosimetry in digital breast tomosynthesis: report of AAPM Tomosynthesis Subcommittee Task Group 223.

Journal Article Med Phys · September 2014 The radiation dose involved in any medical imaging modality that uses ionizing radiation needs to be well understood by the medical physics and clinical community. This is especially true of screening modalities. Digital breast tomosynthesis (DBT) has rece ... Full text Link to item Cite

Development and application of a suite of 4-D virtual breast phantoms for optimization and evaluation of breast imaging systems.

Journal Article IEEE Trans Med Imaging · July 2014 Mammography is currently the most widely utilized tool for detection and diagnosis of breast cancer. However, in women with dense breast tissue, tissue overlap may obscure lesions. Digital breast tomosynthesis can reduce tissue overlap. Furthermore, imagin ... Full text Link to item Cite

Task-based strategy for optimized contrast enhanced breast imaging: analysis of six imaging techniques for mammography and tomosynthesis.

Conference Med Phys · June 2014 PURPOSE: The use of contrast agents in breast imaging has the capability of enhancing nodule detectability and providing physiological information. Accordingly, there has been a growing trend toward using iodine as a contrast medium in digital mammography ... Full text Link to item Cite

Modeling resident error-making patterns in detection of mammographic masses using computer-extracted image features: Preliminary experiments

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2014 Providing high quality mammography education to radiology trainees is essential, as good interpretation skills potentially ensure the highest benefit of screening mammography for patients. We have previously proposed a computer-aided education system that ... Full text Cite

Population of 100 realistic, patient-based computerized breast phantoms for multi-modality imaging research

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2014 Breast imaging is an important area of research with many new Techniques being investigated To further reduce The morbidity and mortality of breast cancer Through early detection. Computerized phantoms can provide an essential Tool To quantitatively compar ... Full text Cite

A second generation of physical anthropomorphic 3D breast phantoms based on human subject data

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2014 Previous fabrication of anthropomorphic breast phantoms has demonstrated Their viability as a model for 2D (mammography) and 3D (tomosynthesis) breast imaging systems. Further development of These models will be essential for The evaluation of breast x-ray ... Full text Cite

A task-based comparison of two reconstruction algorithms for digital breast tomosynthesis

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · January 1, 2014 Digital breast tomosynthesis (DBT) generates 3-D reconstructions of the breast by taking X-Ray projections at various angles around the breast. DBT improves cancer detection as it minimizes tissue overlap that is present in traditional 2-D mammography. In ... Full text Cite

A knowledge-based approach to improving and homogenizing intensity modulated radiation therapy planning quality among treatment centers: an example application to prostate cancer planning.

Journal Article Int J Radiat Oncol Biol Phys · September 1, 2013 PURPOSE: Intensity modulated radiation therapy (IMRT) treatment planning can have wide variation among different treatment centers. We propose a system to leverage the IMRT planning experience of larger institutions to automatically create high-quality pla ... Full text Link to item Cite

Quality assurance and training procedures for computer-aided detection and diagnosis systems in clinical use.

Journal Article Med Phys · July 2013 Computer-aided detection/diagnosis (CAD) is increasingly used for decision support by clinicians for detection and interpretation of diseases. However, there are no quality assurance (QA) requirements for CAD in clinical use at present. QA of CAD is import ... Full text Link to item Cite

Estimating breast density with dual energy mammography: A simple model based on calibration phantoms

Journal Article Progress in Biomedical Optics and Imaging - Proceedings of SPIE · June 3, 2013 Dual energy digital mammography has been used to suppress specific breast tissue, primarily for the purpose of iodine contrast-enhanced imaging. Another application of dual energy digital mammography is to estimate breast density, as defined by the fractio ... Full text Cite

Development of matched virtual and physical breast phantoms based on patient data

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · 2013 Physical phantoms are essential for the development, optimization, and clinical evaluation of x-ray systems. These phantoms are used for various tests such as quality assurance testing, system characterization, reconstruction evaluation, and dosimetry. The ... Full text Cite

Application of a dynamic 4D anthropomorphic breast phantom in contrast-based imaging system optimization: Dual-energy or temporal subtraction?

Journal Article Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) · August 15, 2012 We previously developed a dynamic 4D anthropomorphic breast phantom, which can be used to optimize contrast-based breast imaging systems, accounting for patient variability and contrast kinetics [1]. In this study we aim to compare the performance of contr ... Full text Cite

WE-G-BRCD-06: Knowledge-Based Intensity Modulated Radiotherapy (IMRT) Treatment Planning for Prostate Cancer.

Conference Med Phys · June 2012 PURPOSE: To verify that a knowledge-based approach to intensity modulated radiotherapy (IMRT) treatment planning can create clinically acceptable plans of higher or comparable dosimetric quality than prior clinically approved plans. METHODS: Each case in a ... Full text Link to item Cite

SU-E-T-572: A Plan Quality Metric for Evaluating Knowledge-Based Treatment Plans.

Conference Med Phys · June 2012 PURPOSE: In prostate IMRT treatment planning, the variation in patient anatomy makes it difficult to estimate a priori the potentially achievable extent of dose reduction possible to the rectum and bladder. We developed a mutual information-based framework ... Full text Link to item Cite

Development of a dynamic 4D anthropomorphic breast phantom for contrast-based breast imaging

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · May 4, 2012 Mammography is currently the most widely accepted tool for detection and diagnosis of breast cancer. However, the sensitivity of mammography is reduced in women with dense breast tissue due to tissue overlap, which may obscure lesions. Digital breast tomos ... Full text Cite

3D biopsy for tomosynthesis: Simulation of prior information based reconstruction for dose and artifact reduction

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · May 4, 2012 Accurately targeting of small lesions for success is crucial in breast biopsy. In this paper, we proposed a new 3D tomobased biopsy, which is characterized in being more accurate, easier to perform, lower in dose, and free of metal artifact. In the scout p ... Full text Cite

Task-based strategy for optimized contrast enhanced breast imaging: analysis of six imaging techniques for mammography and tomosynthesis

Conference SPIE Proceedings · February 23, 2012 Full text Cite

Mutual information-based template matching scheme for detection of breast masses: from mammography to digital breast tomosynthesis.

Journal Article J Biomed Inform · October 2011 Development of a computational decision aid for a new medical imaging modality typically is a long and complicated process. It consists of collecting data in the form of images and annotations, development of image processing and pattern recognition algori ... Full text Link to item Cite

Breast tomosynthesis: state-of-the-art and review of the literature.

Journal Article Acad Radiol · October 2011 Full text Link to item Cite

Validation of a 3D hidden-Markov model for breast tissue segmentation and density estimation from MR and tomosynthesis images

Journal Article Proceedings of the 2011 Biomedical Sciences and Engineering Conference: Image Informatics and Analytics in Biomedicine, BSEC 2011 · July 7, 2011 Breast cancer is the most common non-skin cancer and the second leading cause of cancer-related death in women here in the United States. Mammography is the current standard clinical imaging modality for breast cancer screening and diagnosis, and mammograp ... Full text Cite

Segmentation of adipose and glandular tissue for breast tomosynthesis imaging using a 3D hidden-Markov model trained on breast MRIs

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · May 13, 2011 Breast tomosynthesis involves a restricted number of images acquired in an arc in conventional mammography projection geometry. Despite its angular undersampling, tomosynthesis projections are reconstructed into a volume at a dose comparable to mammography ... Full text Cite

Knowledge-based IMRT treatment planning for prostate cancer.

Journal Article Med Phys · May 2011 PURPOSE: To demonstrate the feasibility of using a knowledge base of prior treatment plans to generate new prostate intensity modulated radiation therapy (IMRT) plans. Each new case would be matched against others in the knowledge base. Once the best match ... Full text Link to item Cite

Comparative performance of multiview stereoscopic and mammographic display modalities for breast lesion detection.

Journal Article Med Phys · April 2011 PURPOSE: Mammography is known to be one of the most difficult radiographic exams to interpret. Mammography has important limitations, including the superposition of normal tissue that can obscure a mass, chance alignment of normal tissue to mimic a true le ... Full text Link to item Cite

SU‐E‐T‐851: An Inter‐Institutional Comparison of Knowledge‐Based IMRT Treatment Planning for Prostate Cancer

Conference Medical Physics · January 1, 2011 Purpose: To evaluate the feasibility of using a site‐specific database of prior plans to generate new prostate IMRT plans for cases drawn from an outside institution. Methods: The assembled database consists of 250 retrospective prostate IMRT treatment pla ... Full text Cite

Computer-aided classification of breast masses: performance and interobserver variability of expert radiologists versus residents.

Journal Article Radiology · January 2011 PURPOSE: To evaluate the interobserver variability in descriptions of breast masses by dedicated breast imagers and radiology residents and determine how any differences in lesion description affect the performance of a computer-aided diagnosis (CAD) compu ... Full text Link to item Cite

User modeling for improved computer-aided training in radiology: Initial experience

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · December 1, 2010 Although mammography is an efficient screening modality for breast cancer, interpretation of mammographic images is a difficult task and notable variability between radiologists performance has been documented. A significant factor impacting radiologists d ... Full text Cite

Efﬁcient fourier-wavelet super-resolution.

Journal Article IEEE Trans Image Process · October 2010 Super-resolution (SR) is the process of combining multiple aliased low-quality images to produce a high-resolution high-quality image. Aside from registration and fusion of low-resolution images, a key process in SR is the restoration and denoising of the ... Full text Link to item Cite

The quantitative potential for breast tomosynthesis imaging.

Journal Article Med Phys · March 2010 PURPOSE: Due to its limited angular scan range, breast tomosynthesis has lower resolution in the depth direction, which may limit its accuracy in quantifying tissue density. This study assesses the quantitative potential of breast tomosynthesis using relat ... Full text Link to item Cite

A technique optimization protocol and the potential for dose reduction in digital mammography.

Journal Article Med Phys · March 2010 Digital mammography requires revisiting techniques that have been optimized for prior screen/film mammography systems. The objective of the study was to determine optimized radiographic technique for a digital mammography system and demonstrate the potenti ... Full text Link to item Cite

SU‐GG‐T‐131: A Linear Metric of Knowledge‐Based IMRT Treatment Plan Quality for the Prostate

Conference Medical Physics · January 1, 2010 Purpose: In prostate IMRT treatment planning, the variation in patient anatomy makes it difficult to a priori estimate the maximum extent of dose reduction possible to rectum and bladder. Such an estimation would greatly aid treatment planning by letting c ... Full text Cite

SU‐GG‐T‐134: Knowledge‐Based IMRT Treatment Planning for Prostate Cancer

Conference Medical Physics · January 1, 2010 Purpose: To investigate the potential of utilizing a knowledge‐base of clinically approved plans to develop semi‐automated IMRT treatment plans for prostate cancer. Method and Materials: We assembled a database of 100 prostate IMRT treatment plans and deve ... Full text Cite

WE‐A‐201B‐04: Reducing Dose in Breast Tomosynthesis Using Bayesian Image Estimation

Conference Medical Physics · January 1, 2010 Purpose: To reduce dose of breast tomosynthesis imaging by applying Bayesian Image Estimation (BIE) processing to projection images. BIE has been shown previously to reduce scatter and improve image signal‐to‐noise ratios without an associated loss of reso ... Full text Cite

SU‐GG‐I‐154: Evaluation of Quantitative Potential of Breast Tomosynthesis Using a Voxelized Anthropomorphic Breast Phantom

Conference Medical Physics · January 1, 2010 Purpose: To assess the quantitative potential of breast tomosynthesis by estimating the percent density of voxelized anthropomorphic breast phantoms. Method and Materials: A Siemens breast tomosynthesis system was modeled using Monte Carlo methods and a vo ... Full text Cite

Optimized image acquisition for breast tomosynthesis in projection and reconstruction space.

Journal Article Med Phys · November 2009 Breast tomosynthesis has been an exciting new development in the field of breast imaging. While the diagnostic improvement via tomosynthesis is notable, the full potential of tomosynthesis has not yet been realized. This may be attributed to the dependency ... Full text Link to item Cite

Computerized 3D breast phantom with enhanced High-Resolution detail

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · June 15, 2009 We previously proposed a three-dimensional computerized breast phantom that combines empirical data with the flexibility of mathematical models1. The goal of this project is to enhance the breast phantom to include a more detailed anatomy than currently vi ... Full text Cite

Optimized lesion detection in breast tomosynthesis

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · June 15, 2009 While diagnostic improvement via breast tomosynthesis has been notable, the full potential of tomosynthesis has not yet been realized. This is because of the complex task of optimizing multiple parameters that constitute image acquisition and thus affect t ... Full text Cite

Can compression be reduced for breast tomosynthesis? Monte carlo study on mass and microcalcification conspicuity in tomosynthesis.

Journal Article Radiology · June 2009 PURPOSE: To assess, in a voxelized anthropomorphic breast phantom, how the conspicuity of breast masses and microcalcifications may be affected by applying reduced breast compression in tomosynthesis. MATERIALS AND METHODS: A breast tomosynthesis system wa ... Full text Link to item Cite

Do serum biomarkers really measure breast cancer?

Journal Article BMC Cancer · May 28, 2009 BACKGROUND: Because screening mammography for breast cancer is less effective for premenopausal women, we investigated the feasibility of a diagnostic blood test using serum proteins. METHODS: This study used a set of 98 serum proteins and chose diagnostic ... Full text Link to item Cite

Towards optimized acquisition scheme for multiprojection correlation imaging of breast cancer.

Journal Article Acad Radiol · April 2009 RATIONALE AND OBJECTIVES: Correlation imaging (CI) is a form of multiprojection imaging in which multiple images of a patient are acquired from slightly different angles. Information from these images is combined to make the final diagnosis. A critical fac ... Full text Link to item Cite

MO‐FF‐A4‐01: Evaluation of Background Trend Correction Technique in Breast Tomosynthesis Quantitation

Conference Medical Physics · January 1, 2009 Purpose: The main shortcoming of breast tomosynthesis (tomo) imaging when compared to CT is poor resolution in the depth direction and the associated difficulty in quantifying tissue density. This study will assess the quantitative potential of breast tomo ... Full text Cite

Efficient restoration and enhancement of super-resolved X-ray images

Chapter · December 1, 2008 Our previous work demonstrates the ability to reconstruct a single higher resolution image from fusing a collection of multiple extremely low-dosage aliased X-ray images. While this computationally efficient method eliminates aliasing artifacts associated ... Full text Cite

Mass detectability in dedicated breast CT: A simulation study with the application of volume noise removal

Conference 8th IEEE International Conference on BioInformatics and BioEngineering, BIBE 2008 · December 1, 2008 Dedicated breast Computed Tomography (CT) is an emerging new technique for breast cancer imaging. Breast CT data can be acquired at a dose level as low as the conventional two-view mammography. Since the dose is equally split into hundreds of projection vi ... Full text Cite

Multi-projection correlation imaging as a new diagnostic tool for improved breast cancer detection

Conference Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) · September 9, 2008 Multi-projection imaging technique offers an advantage over single projection imaging techniques in rendering pathology that may be surrounded by a complex cloud of anatomical structures. The process of harnessing the geometrical and statistical dependence ... Full text Cite

Knowledge transfer across breast cancer screening modalities: A pilot study using an information-theoretic CADe system for mass detection

Conference Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) · September 9, 2008 We have performed a series of experiments to assess whether a featureless, knowledge-based CADe system that relies on information theoretic principles is capable of transferring knowledge across cases acquired with different imaging modalities. Typical fea ... Full text Cite

Assessment of low energies and slice depth in the quantification of breast tomosynthesis

Conference Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) · September 9, 2008 This study attempts to assess the quantitative potential of breast tomosynthesis imaging. Tomosynthesis might be a feasible replacement for digital mammography, so it is worthwhile to consider whether it can be quantitative like computed tomography (CT), w ... Full text Cite

Effect of similarity metrics and ROI sizes in featureless computer aided detection of breast masses in tomosynthesis

Conference Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) · September 9, 2008 Tomosynthesis as a technique is being developed and studied with the goal of overcoming mammography's limitations due to overlying tissue. Various algorithms exist for tomosynthesis datasets including a novel Computer Aided Detection (CADe) algorithm using ... Full text Cite

Automated breast mass detection in 3D reconstructed tomosynthesis volumes: a featureless approach.

Journal Article Med Phys · August 2008 The purpose of this study was to propose and implement a computer aided detection (CADe) tool for breast tomosynthesis. This task was accomplished in two stages-a highly sensitive mass detector followed by a false positive (FP) reduction stage. Breast tomo ... Full text Link to item Cite

Optimized acquisition scheme for multi-projection correlation imaging of breast cancer

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · June 2, 2008 We are reporting the optimized acquisition scheme of multi-projection breast Correlation Imaging (CI) technique, which was pioneered in our lab at Duke University. CI is similar to tomosynthesis in its image acquisition scheme. However, instead of analyzin ... Full text Cite

Computer aided detection of breast masses in tomosynthesis reconstructed volumes using information-theoretic similarity measures

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · June 2, 2008 The purpose of this project is to study two Computer Aided Detection (CADe) systems for breast masses for digital tomosynthesis using reconstructed slices. This study used eighty human subject cases collected as part of on-going clinical trials at Duke Uni ... Full text Cite

Optimization of exposure parameters in full field digital mammography.

Journal Article Med Phys · June 2008 Optimization of exposure parameters (target, filter, and kVp) in digital mammography necessitates maximization of the image signal-to-noise ratio (SNR), while simultaneously minimizing patient dose. The goal of this study is to compare, for each of the maj ... Full text Link to item Cite

Three-dimensional computer generated breast phantom based on empirical data

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · May 14, 2008 The goal of this work is to create a detailed three-dimensional (3D) digital breast phantom based on empirical data and to incorporate it into the four-dimensional (4D) NCAT phantom, a computerized model of the human anatomy widely used in imaging research ... Full text Cite

Toward quantification of breast tomosynthesis imaging

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · May 14, 2008 Due to the high prevalence of breast cancer among women, much is being done to detect breast cancer earlier and more accurately. In current clinical practice, the most widely-used mode of breast imaging is mammography. Its main advantages are high sensitiv ... Full text Cite

Neutron-stimulated emission computed tomography of a multi-element phantom.

Journal Article Phys Med Biol · May 7, 2008 This paper describes the implementation of neutron-stimulated emission computed tomography (NSECT) for non-invasive imaging and reconstruction of a multi-element phantom. The experimental apparatus and process for acquisition of multi-spectral projection d ... Full text Link to item Cite

Dedicated breast computed tomography: volume image denoising via a partial-diffusion equation based technique.

Journal Article Med Phys · May 2008 Dedicated breast computed tomography (CT) imaging possesses the potential for improved lesion detection over conventional mammograms, especially for women with dense breasts. The breast CT images are acquired with a glandular dose comparable to that of sta ... Full text Link to item Cite

A mathematical model platform for optimizing a multiprojection breast imaging system.

Journal Article Med Phys · April 2008 Multiprojection imaging is a technique in which a plurality of digital radiographic images of the same patient are acquired within a short interval of time from slightly different angles. Information from each image is combined to determine the final diagn ... Full text Link to item Cite

Point/Counterpoint. Cone beam x-ray CT will be superior to digital x-ray tomosynthesis in imaging the breast and delineating cancer.

Journal Article Med Phys · February 2008 Full text Link to item Cite

TU‐D‐342‐02: What Every Medical Physicist Should Know About Breast Tomosynthesis

Conference Medical Physics · January 1, 2008 Digital tomosynthesis (or “tomo”) is revolutionizing breast imaging. Based on modified full‐field digital mammography systems, breast tomo can achieve limited‐angle cone‐beam CT imaging which produces 3D slice images of the breast. This addresses the probl ... Full text Cite

Training neural network classifiers for medical decision making: the effects of imbalanced datasets on classification performance.

Journal Article Neural Netw · 2008 This study investigates the effect of class imbalance in training data when developing neural network classifiers for computer-aided medical diagnosis. The investigation is performed in the presence of other characteristics that are typical among medical d ... Full text Link to item Cite

Efficient Restoration and Enhancement of Super-resolved X-ray Images

Conference 2008 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, PROCEEDINGS · January 1, 2008 Link to item Cite

Impulse response and Modulation Transfer Function analysis for Shift-And-Add and Back Projection image reconstruction algorithms in Digital Breast Tomosynthesis (DBT).

Journal Article Int J Funct Inform Personal Med · 2008 Breast cancer is second only to lung cancer as the leading cause of non-preventable cancer death in women. Digital Breast Tomosynthesis (DBT) is a promising technique to improve early breast cancer detection. In this paper, we present the impulse response ... Full text Link to item Cite

A comparison between traditional shift-and-add (SAA) and point-by-point back projection (BP) - Relevance to morphology of microcalcifications for isocentric motion in Digital Breast tomosynthesis (DBT)

Journal Article Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE · December 1, 2007 Digital breast tomosynthesis (DBT) is a three-dimensional imaging technique providing an arbitrary set of reconstruction planes in the breast with limited series of projection images. This paper describes a comparison between traditional shift-and-add (SAA ... Full text Cite

Efficient registration of aliased x-ray images

Other Conference Record - Asilomar Conference on Signals, Systems and Computers · December 1, 2007 Multiframe image reconstruction produces images beyond the native resolution of a digital image sensor by way of accurate sub-pixel registration of aliased images. We present a novel multiframe registration approach for the purpose of enhancing resolution ... Full text Cite

Decision fusion of circulating markers for breast cancer detection in premenopausal women

Chapter · December 1, 2007 Current mammographic screeningfor breast cancer is less effective for younger women. To complement mammography for premenopausal women, we investigated the feasibility screening test using 98 blood serum proteins. Because the data set was very noisy and co ... Full text Cite

Feasibility study of breast tomosynthesis CAD system

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · October 18, 2007 The purpose of this study was to investigate feasibility of computer-aided detection of masses and calcification clusters in breast tomosynthesis images and obtain reliable estimates of sensitivity and false positive rate on an independent test set. Automa ... Full text Cite

Initial human subject results for breast Bi-plane correlation imaging technique

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · October 18, 2007 Computer aided detection (CADe) systems often present multiple false-positives per image in projection mammography due to overlapping anatomy. To reduce the number of such false-positives, we propose performing CADe on image pairs acquired using a bi-plane ... Full text Cite

Breast mass detection in tomosynthesis projection images using information-theoretic similarity measures

Journal Article Progress in Biomedical Optics and Imaging - Proceedings of SPIE · October 18, 2007 The purpose of this project is to study Computer Aided Detection (CADe) of breast masses for digital tomosynthesis. It is believed that tomosynthesis will show improvement over conventional mammography in detection and characterization of breast masses by ... Full text Cite

Methodology of NEQ (f) analysis for optimization and comparison of digital breast tomosynthesis acquisition techniques and reconstruction algorithms

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · October 15, 2007 As a new three-dimensional imaging technique, digital breast tomosynthesis allows the reconstruction of an arbitrary set of planes in the breast from a limited-angle series of projection images. Though several tomosynthesis algorithms have been proposed, n ... Full text Cite

Visual image quality metrics for optimization of breast tomosynthesis acquisition technique

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · October 15, 2007 Breast tomosynthesis is currently an investigational imaging technique requiring optimization of its many combinations of data acquisition and image reconstruction parameters for optimum clinical use. In this study, the effects of several acquisition param ... Full text Cite

On the development of a Gaussian noise model for scatter compensation

Conference Progress in Biomedical Optics and Imaging - Proceedings of SPIE · October 15, 2007 The underlying mechanism in projection radiography as well as in computed tomography (CT) is the accumulative attenuation of a pencil x-ray beam along a straight line. However, when a portion of photons is deviated from their original path by scattering, i ... Full text Cite

Importance of point-by-point back projection correction for isocentric motion in digital breast tomosynthesis: relevance to morphology of structures such as microcalcifications.

Journal Article Med Phys · October 2007 Digital breast tomosynthesis is a three-dimensional imaging technique that provides an arbitrary set of reconstruction planes in the breast from a limited-angle series of projection images acquired while the x-ray tube moves. Traditional shift-and-add (SAA ... Full text Link to item Cite

Information-theoretic CAD system in mammography: entropy-based indexing for computational efficiency and robust performance.

Journal Article Med Phys · August 2007 We have previously presented a knowledge-based computer-assisted detection (KB-CADe) system for the detection of mammographic masses. The system is designed to compare a query mammographic region with mammographic templates of known ground truth. The templ ... Full text Link to item Cite

Breast mass lesions: computer-aided diagnosis models with mammographic and sonographic descriptors.

Journal Article Radiology · August 2007 PURPOSE: To retrospectively develop and evaluate computer-aided diagnosis (CAD) models that include both mammographic and sonographic descriptors. MATERIALS AND METHODS: Institutional review board approval was obtained for this HIPAA-compliant study. A wai ... Full text Link to item Cite

Incorporation of a Laguerre-Gauss channelized Hotelling observer for false-positive reduction in a mammographic mass CAD system.

Journal Article J Digit Imaging · June 2007 Previously, we developed a simple Laguerre-Gauss (LG) channelized Hotelling observer (CHO) for incorporation into our mass computer-aided detection (CAD) system. This LG-CHO was trained using initial detection suspicious region data and was empirically opt ... Full text Link to item Cite

Multiprojection correlation imaging for improved detection of pulmonary nodules.

Journal Article AJR Am J Roentgenol · May 2007 OBJECTIVE: The purpose of this study was the development and preliminary evaluation of multiprojection correlation imaging with 3D computer-aided detection (CAD) on chest radiographs for cost- and dose-effective improvement of early detection of pulmonary ... Full text Link to item Cite

Circuit-based SEM contour OPC model calibration

Journal Article SPIE Proceedings · March 16, 2007 Full text Cite

Neutron stimulated emission computed tomography: Background corrections

Journal Article Nuclear Instruments and Methods in Physics Research, Section B: Beam Interactions with Materials and Atoms · January 1, 2007 Neutron stimulated emission computed tomography (NSECT) is an imaging technique that provides an in-vivo tomographic spectroscopic image of the distribution of elements in a body. To achieve this, a neutron beam illuminates the body. Nuclei in the body alo ... Full text Cite

Evaluation of information-theoretic similarity measures for content-based retrieval and detection of masses in mammograms.

Journal Article Med Phys · January 2007 The purpose of this study was to evaluate image similarity measures employed in an information-theoretic computer-assisted detection (IT-CAD) scheme. The scheme was developed for content-based retrieval and detection of masses in screening mammograms. The ... Full text Link to item Cite

MO‐D‐L100F‐03: New Developments in Digital Breast Tomosynthesis

Conference Medical Physics · January 1, 2007 Digital tomosynthesis is one of the most exciting recent developments in breast imaging. By modifying existing full field digital mammography systems, one can achieve this type of limited‐angle cone‐beam CT imaging which produces 3D slice images of the bre ... Full text Cite

TU‐B‐M100J‐01: Optimizing Mammography Image Quality and Dose: X‐Ray Spectrum and Exposure Parameter Selection

Conference Medical Physics · January 1, 2007 Optimization of exposure parameters (target, filter, and kVp) in digital mammography necessitates maximization of the image signal‐to‐noise ratio (SNR), while simultaneously minimizing patient dose. The goal of this talk is to compare, for each of the majo ... Full text Cite

Optimized approach to decision fusion of heterogeneous data for breast cancer diagnosis.

Journal Article Med Phys · August 2006 As more diagnostic testing options become available to physicians, it becomes more difficult to combine various types of medical information together in order to optimize the overall diagnosis. To improve diagnostic performance, here we introduce an approa ... Full text Link to item Cite

Introduction to neutron stimulated emission computed tomography.

Journal Article Phys Med Biol · July 21, 2006 Neutron stimulated emission computed tomography (NSECT) is presented as a new technique for in vivo tomographic spectroscopic imaging. A full implementation of NSECT is intended to provide an elemental spectrum of the body or part of the body being interro ... Full text Link to item Cite

Rotating slat collimator design for high-energy near-field imaging

Journal Article Progress in Biomedical Optics and Imaging - Proceedings of SPIE · July 3, 2006 Certain elements (such as Fe, Cu, Zn, etc.) are vital to the body and an imbalance of such elements can either be a symptom or cause of certain pathologies. Neutron Stimulated Emission Computed Tomography (NSECT) is a spectroscopic imaging technique whereb ... Full text Cite

Noise power spectrum analysis for several digital breast tomosynthesis reconstruction algorithms

Journal Article Progress in Biomedical Optics and Imaging - Proceedings of SPIE · June 30, 2006 Digital breast tomosynthesis is a three-dimensional imaging technique that allows the reconstruction of an arbitrary set of planes in the breast from limited-angle series of projection images. Though several tomosynthesis algorithms have been proposed, no ... Full text Cite

Gaussian frequency blending algorithm with Matrix Inversion Tomosynthesis (MITS) and Filtered Back Projection (FBP) for better digital breast tomosynthesis reconstruction

Journal Article Progress in Biomedical Optics and Imaging - Proceedings of SPIE · June 30, 2006 Breast cancer is a major problem and the most common cancer among women. The nature of conventional mammography makes it very difficult to distinguish a cancer from overlying breast tissues. Digital Tomosynthesis refers to a three-dimensional imaging techn ... Full text Cite

Breast cancer diagnosis using neutron stimulated emission computed tomography: Dose and count requirements

Journal Article Progress in Biomedical Optics and Imaging - Proceedings of SPIE · June 30, 2006 Neutron Stimulated Emission Computed Tomography (NSECT) was evaluated as a potential technique for breast cancer diagnosis. NSECT can form a 3D tomographic image with an elemental (isotopic) spectrum provided at each reconstructed voxel. The target is illu ... Full text Cite

The effect of data set size on computer-aided diagnosis of breast cancer: Comparing decision fusion to a linear discriminant

Journal Article Progress in Biomedical Optics and Imaging - Proceedings of SPIE · June 23, 2006 Data sets with relatively few observations (cases) in medical research are common, especially if the data are expensive or difficult to collect. Such small sample sizes usually do not provide enough information for computer models to learn data patterns we ... Full text Cite

Mass detection in mammographic ROIs using Watson filters

Journal Article Progress in Biomedical Optics and Imaging - Proceedings of SPIE · June 22, 2006 Human vision models have been shown to capture the response of the visual system; their incorporation into the classification stage of a Computer Aided Detection system could improve performance. This study seeks to improve the performance of an automated ... Full text Cite

Computer-aided diagnosis in breast imaging: Where do we go after detection?

Chapter · April 10, 2006 Full text Cite

Using computational intelligence for computer-aided diagnosis of screen-film mammograms

Chapter · April 10, 2006 Full text Cite

Beam optimization for digital mammography - II

Journal Article Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) · January 1, 2006 Optimization of acquisition technique factors (target, filter, and kVp) in digital mammography is required for maximization of the image SNR, while minimizing patient dose. The goal of this study is to compare, for each of the major commercially available ... Full text Cite

SU‐FF‐I‐21: Two‐Dimensional Shift‐And‐Add (SAA) Algorithm for Digital Breast Tomosynthesis Reconstruction

Conference Medical Physics · January 1, 2006 Purpose: To investigate a two‐dimensional Shift‐And‐Add algorithm for three‐dimensional digital breast tomosynthsis reconstruction to correct for defects existing in the traditional Shift‐And‐Add algorithm that calculates only one‐dimensional shift amount ... Full text Cite

Issues in assessing multi-institutional performance of BI-RADS-based CAD systems

Journal Article Progress in Biomedical Optics and Imaging - Proceedings of SPIE · August 25, 2005 The purpose of this study was to investigate factors that impact the generalization of breast cancer computer-aided diagnosis (CAD) systems that utilize the Breast Imaging Reporting and Data System (BI-RADS™). Data sets from four institutions were analyzed ... Full text Cite

Detector evaluation of a prototype amorphous selenium-based full field digital mammography system

Journal Article Progress in Biomedical Optics and Imaging - Proceedings of SPIE · August 25, 2005 This study evaluated the physical performance of a selenium-based direct full-field digital mammography prototype detector (Siemens Mammomat Novation DR), including the pixel value vs. exposure linearity, the modulation transfer function (MTF), the normali ... Full text Cite

Characterization of scatter radiation of a breast phantom on siemens prototype FFDM with and without an anti-scatter grid

Journal Article Progress in Biomedical Optics and Imaging - Proceedings of SPIE · August 25, 2005 In this study, the beam stop technique was applied to obtain the scatter fraction values for an anthropomorphic breast phantom on a flat-panel full field mammography system. The phantom was equivalent to a compressed breast of 5 cm thickness with 50% gland ... Full text Cite

Impulse response analysis for several digital tomosynthesis mammography reconstruction algorithms

Journal Article Progress in Biomedical Optics and Imaging - Proceedings of SPIE · August 25, 2005 Digital tomosynthesis mammography algorithms allow reconstructions of arbitrary planes in the breast from limited-angle series of projection images as the x-ray source moves along an arc above the breast. Though several tomosynthesis algorithms have been p ... Full text Cite

Computer aid for decision to biopsy breast masses on mammography: validation on new cases.

Journal Article Acad Radiol · June 2005 RATIONALE AND OBJECTIVES: The purpose of this study was to validate the performance of a previously developed computer aid for breast mass classification for mammography on a new, independent database of cases not used for algorithm development. MATERIALS ... Full text Link to item Cite

Comparative scatter and dose performance of slot-scan and full-field digital chest radiography systems.

Journal Article Radiology · June 2005 PURPOSE: To evaluate the scatter, dose, and effective detective quantum efficiency (DQE) performance of a slot-scan digital chest radiography system compared with that of a full-field digital radiography system. MATERIALS AND METHODS: Scatter fraction of a ... Full text Link to item Cite

Accuracy of segmentation of a commercial computer-aided detection system for mammography.

Journal Article Radiology · May 2005 PURPOSE: To assess the accuracy of segmentation in a commercially available computer-aided detection (CAD) system. MATERIALS AND METHODS: Approval for this study was obtained from the authors' institutional review board. Informed consent was not required b ... Full text Link to item Cite

Physical characterization of a prototype selenium-based full field digital mammography detector.

Journal Article Med Phys · February 2005 The purpose of this study was to measure experimentally the physical performance of a prototype mammographic imager based on a direct detection, flat-panel array design employing an amorphous selenium converter with 70 microm pixels. The system was charact ... Full text Link to item Cite

Digital breast tomosynthesis using an amorphous selenium flat panel detector

Journal Article Progress in Biomedical Optics and Imaging - Proceedings of SPIE · 2005 A prototype breast tomosynthesis system* has been developed, allowing a total angular view of ±25°. The detector used in this system is an amorphous selenium direct-conversion digital flat-panel detector suitable for digital tomosynthesis. The s ... Full text Link to item Cite

A framework for optimising the radiographic technique in digital X-ray imaging.

Journal Article Radiat Prot Dosimetry · 2005 The transition to digital radiology has provided new opportunities for improved image quality, made possible by the superior detective quantum efficiency and post-processing capabilities of new imaging systems, and advanced imaging applications, made possi ... Full text Link to item Cite

Bayesian networks of BI-RADS™ descriptors for breast lesion Classification

Journal Article Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings · December 1, 2004 We investigated Bayesian network structure learning and probability estimation from mammographic feature data in order to classify breast lesions into different pathological categories. We compared the learned networks to naïve Bayes classifiers, which are ... Cite

Computer-aided detection in screening mammography: variability in cues.

Journal Article Radiology · November 2004 PURPOSE: To evaluate the variability of true-positive and false-positive cues by using a commercially available computer-aided detection (CAD) system for analysis of 50 malignancies in a screening population. MATERIALS AND METHODS: Fifty breast cancers det ... Full text Link to item Cite

New results in computer aided diagnosis (CAD) of breast cancer using a recently developed SVM/GRNN oracle hybrid

Journal Article Proceedings of SPIE - The International Society for Optical Engineering · October 27, 2004 Breast cancer is second only to lung cancer as a tumor-related cause of death in women. Currently, the method of choice for the early detection of breast cancer is mammography. While sensitive to the detection of non palpable breast lesions, its positive p ... Full text Cite

Breast cancer classification improvements using a new kernel function with evolutionary-programming-configured support vector machines

Journal Article Proceedings of SPIE - The International Society for Optical Engineering · October 27, 2004 Mammography is an effective tool for the early detection of breast cancer; however, most women referred for biopsy based on mammographic findings do not, in fact, have cancer. This study is part of an ongoing effort to reduce the number of benign cases ref ... Full text Cite

Fundamental imaging characteristics of a slot-scan digital chest radiographic system.

Journal Article Med Phys · September 2004 Our purpose in this study was to evaluate the fundamental image quality characteristics of a new slot-scan digital chest radiography system (ThoraScan, Delft Imaging Systems/Nucletron, Veenendaal, The Netherlands). The linearity of the system was measured ... Full text Link to item Cite

Computer-aided classification of breast masses using mammogram, ultrasound, and clinical inputs

Conference AMERICAN JOURNAL OF ROENTGENOLOGY · January 1, 2004 Link to item Cite

Computer-aided detection (CAD) in screening mammography: sensitivity of commercial CAD systems for detecting architectural distortion.

Journal Article AJR Am J Roentgenol · October 2003 OBJECTIVE: Computer-aided detection (CAD) algorithms have successfully revealed breast masses and microcalcifications on screening mammography. The purpose of our study was to evaluate the sensitivity of commercially available CAD systems for revealing arc ... Full text Link to item Cite

Improving the predictive value of mammography using a specialized evolutionary programming hybrid and fitness functions

Journal Article Proceedings of SPIE - The International Society for Optical Engineering · September 15, 2003 Mammography is an effective tool for the early detection of breast cancer; however, most women referred for biopsy based on mammographic findings do not, have cancer. This study is part of an ongoing effort to reduce the number of benign cases referred for ... Full text Cite

Application of support vector machines to breast cancer screening using mammogram and clinical history data

Journal Article Proceedings of SPIE - The International Society for Optical Engineering · September 15, 2003 The objectives of this paper are to discuss: (1) the development and testing of a new Evolutionary Programming (EP) method to optimally configure Support Vector Machine (SVM) parameters for facilitating the diagnosis of breast cancer; (2) evaluation of EP ... Full text Cite

Prediction of breast biopsy outcome using a likelihood ratio classifier and biopsy cases from two medical centers

Journal Article Proceedings of SPIE - The International Society for Optical Engineering · September 15, 2003 Potential malignancy of a mammographie lesion can be assessed using the mathematically optimal likelihood ratio (LR) from signal detection theory. We developed a LR classifier for prediction of breast biopsy outcome of mammographie masses from BI-RADS find ... Full text Cite

Computer-aided classification of breast microcalcification clusters: Merging of features from image processing and radiologists

Journal Article Proceedings of SPIE - The International Society for Optical Engineering · September 15, 2003 We developed an ensemble classifier for the task of computer-aided diagnosis of breast microcalcification clusters, which are very challenging to characterize for radiologists and computer models alike. The purpose of this study is to help radiologists ide ... Full text Cite

Validation of a constraint satisfaction neural network for breast cancer diagnosis: New results from 1,030 cases

Journal Article Proceedings of SPIE - The International Society for Optical Engineering · September 15, 2003 Previously, we presented a Constraint Satisfaction Neural Network (CSNN) to predict the outcome of breast biopsy using mammographic and clinical findings. Based on 500 cases, the study showed that CSNN was able to operate not only as a predictive but also ... Full text Cite

Application of likelihood ratio to classification of mammographic masses; performance comparison to case-based reasoning.

Journal Article Med Phys · May 2003 The likelihood ratio (LR) is an optimal approach for deciding which of two alternate hypotheses best describes a given situation. We adopted this formalism for predicting whether biopsy results of mammographic masses will be benign or malignant, aiming to ... Full text Link to item Cite

Self-organizing map for cluster analysis of a breast cancer database.

Journal Article Artif Intell Med · February 2003 The purpose of this study was to identify and characterize clusters in a heterogeneous breast cancer computer-aided diagnosis database. Identification of subgroups within the database could help elucidate clinical trends and facilitate future model buildin ... Full text Link to item Cite

Improving mammogram screening using a bank of support vector machines (SVMs)

Journal Article Intelligent Engineering Systems Through Artificial Neural Networks · December 1, 2002 The focus of this study was to build and evaluate a new bank of SVM designs to address the problem of high false positives that currently results from mammogram screening,. The basis of the design is to partition the BIRADS™ varibles into three separate ca ... Cite

Using evolutionary programming to configure support vector machines for the diagnosis of breast cancer

Journal Article Intelligent Engineering Systems Through Artificial Neural Networks · December 1, 2002 Support Vector Machines(s) (SVMs) are new machine intelligence paradigms that use the Structural Risk Minimization (SRM) concept to develop learning machines. SVMs can always be trained to provide global minima, given that the leaning machine parameters ar ... Cite

Differences between computer-aided diagnosis of breast masses and that of calcifications.

Journal Article Radiology · May 2002 PURPOSE: To compare the performance of a computer-aided diagnosis (CAD) system for diagnosis of previously detected lesions, based on radiologist-extracted findings on masses and calcifications. MATERIALS AND METHODS: A feed-forward, back-propagation artif ... Full text Link to item Cite

Parameter optimization of a computer-aided diagnosis scheme for the segmentation of microcalcification clusters in mammograms.

Journal Article Med Phys · April 2002 Our purpose in this study is to develop a parameter optimization technique for the segmentation of suspicious microcalcification clusters in digitized mammograms. In previous work, a computer-aided diagnosis (CAD) scheme was developed that used local histo ... Full text Link to item Cite

Outcome analysis of patients with acute pancreatitis by using an artificial neural network.

Journal Article Acad Radiol · April 2002 RATIONALE AND OBJECTIVES: The authors performed this study to evaluate the ability of an artificial neural network (ANN) that uses radiologic and laboratory data to predict the outcome in patients with acute pancreatitis. MATERIALS AND METHODS: An ANN was ... Full text Link to item Cite

Perceptron error surface analysis: a case study in breast cancer diagnosis.

Journal Article Comput Biol Med · March 2002 Perceptrons are typically trained to minimize mean square error (MSE). In computer-aided diagnosis (CAD), model performance is usually evaluated according to other more clinically relevant measures. The purpose of this study was to investigate the relation ... Full text Link to item Cite

Cross-institutional evaluation of BI-RADS predictive model for mammographic diagnosis of breast cancer.

Journal Article AJR Am J Roentgenol · February 2002 OBJECTIVE: Given a predictive model for identifying very likely benign breast lesions on the basis of Breast Imaging Reporting and Data System (BI-RADS) mammographic findings, this study evaluated the model's ability to generalize to a patient data set fro ... Full text Link to item Cite

Performance tradeoff between evolutionary computation (EC)/adaptive boosting (AB) hybrid and support vector machine breast cancer classification paradigms

Journal Article Proceedings of the 2002 Congress on Evolutionary Computation, CEC 2002 · January 1, 2002 This paper describes a breast cancer classification performance trade-off analysis using two computational intelligence paradigms. The first, an evolutionary programming (EP)/adaptive boosting (AB) based hybrid, intelligently combines the outputs from an i ... Full text Cite

Cluster analysis of BI-RADS™ descriptions of biopsy-proven breast lesions

Journal Article Proceedings of SPIE - The International Society for Optical Engineering · January 1, 2002 The purpose of this study was to identify and characterize clusters in a heterogeneous breast cancer computer-aided diagnosis database. Identification of subgroups within the database could help elucidate clinical trends and facilitate future model buildin ... Full text Cite

Application of support vector machines to breast cancer screening using mammogram and history data

Journal Article Proceedings of SPIE - The International Society for Optical Engineering · January 1, 2002 Support Vector Machines (SVMs) are a new and radically different type of classifiers and learning machines that use a hypothesis space of linear functions in a high dimensional feature space. This relatively new paradigm, based on Statistical Learning theo ... Full text Cite

Computerized classification of suspicious regions in chest radiographs using subregion Hotelling observers.

Journal Article Med Phys · December 2001 We propose to investigate the use of subregion Hotelling observers (SRHOs) in conjunction with perceptrons for the computerized classification of suspicious regions in chest radiographs for being nodules requiring follow up. Previously, 239 regions of inte ... Full text Link to item Cite

A neural network approach to breast cancer diagnosis as a constraint satisfaction problem.

Journal Article Med Phys · May 2001 A constraint satisfaction neural network (CSNN) approach is proposed for breast cancer diagnosis using mammographic and patient history findings. Initially, the diagnostic decision to biopsy was formulated as a constraint satisfaction problem. Then, an ass ... Full text Link to item Cite

New results in breast cancer classification obtained from an evolutionary computation/adaptive boosting hybrid using mammogram and history data

Conference SMCia 2001 - Proceedings of the 2001 IEEE Mountain Workshop on Soft Computing in Industrial Applications · January 1, 2001 A new neural network technology was developed to improve the diagnosis of breast cancer using mammogram findings. The paradigm, adaptive boosting (AB), uses a markedly different theory in solving the computational intelligence (CI) problem. AB, a new machi ... Full text Cite

Application of adaptive boosting to EP-derived multi-layer feedforward neural networks (MLFN) to improve benign/malignant breast cancer classification

Journal Article Proceedings of SPIE - The International Society for Optical Engineering · January 1, 2001 A new neural network technology was developed for improving the benign/malignant diagnosis of breast cancer using mammogram findings. A new paradigm, Adaptive Boosting (AB), uses a markedly different theory in solutioning Computational Intelligence (CI) pr ... Full text Cite

Application of evolutionary computation and neural network hybrids for breast cancer classification using mammogram and history data

Journal Article Proceedings of the IEEE Conference on Evolutionary Computation, ICEC · January 1, 2001 Mammography is the modality of choice for the early detection of breast cancer, primarily because of its sensitivity to the detection of breast cancer. However, because of its high rate of false positive predictions, a large number of biopsies of benign le ... Cite

Computer-aided detection of lung nodules in chest radiographs using sub-region Hotelling observers

Conference RADIOLOGY · 2001 Cite

Application of a new Evolutionary Programming/Adaptive Boosting hybrid to breast cancer diagnosis

Journal Article Proceedings of the IEEE Conference on Evolutionary Computation, ICEC · December 3, 2000 A new Evolutionary Programming/Adaptive Boosting (EP/AB) neural network hybrid was investigated to measure the hybrid performance improvement as obtained when using an EP-only derived neural network as a baseline. By combining input variables consisting of ... Cite

Case-based reasoning computer algorithm that uses mammographic findings for breast biopsy decisions.

Journal Article AJR Am J Roentgenol · November 2000 OBJECTIVE: We present case-based reasoning computer software developed from mammographic findings to provide support for the clinical decision to perform biopsy of the breast. SUBJECTS AND METHODS: The case-based reasoning system is designed to support the ... Full text Link to item Cite

<title>Use of a constraint satisfaction neural network for breast cancer diagnosis and dynamic scenarios simulation</title>

Journal Article SPIE Proceedings · June 6, 2000 Full text Cite

Application of a GRNN oracle to the intelligent combination of several breast cancer benign/malignant predictive paradigms

Journal Article Proc. SPIE - Int. Soc. Opt. Eng. (USA) · 2000 The General Regression Neural Network (GRNN) is well known to be an extremely effective prediction model in a wide variety of problems. It has been recently established that in many prediction problems, the results obtained by intelligently combining the o ... Cite

Segmentation of suspicious clustered microcalcifications in mammograms.

Journal Article Med Phys · January 2000 We have developed a multistage computer-aided diagnosis (CAD) scheme for the automated segmentation of suspicious microcalcification clusters in digital mammograms. The scheme consisted of three main processing steps. First, the breast region was segmented ... Full text Link to item Cite

Evolutionary programming technique for reducing complexity of artificial neural networks for breast cancer diagnosis

Journal Article Proceedings of SPIE - The International Society for Optical Engineering · January 1, 2000 An evolutionary programming (EP) technique was investigated to reduce the complexity of artificial neural network (ANN) models that predict the outcome of mammography-induced breast biopsy. By combining input variables consisting of mammography lesion desc ... Cite

Application of a GRNN ORACLE to the intelligent combination of several breast cancer benign/malignant predictive paradigms

Journal Article Proceedings of SPIE - The International Society for Optical Engineering · 2000 The General Regression Neural Network (GRNN) is well known to be an extremely effective prediction model in a wide variety of problems. It has been recently established that in many prediction problems, the results obtained by intelligently combining the o ... Cite

Evolutionary programming technique for reducing complexity of artificial neural networks for breast cancer diagnosis

Journal Article Proceedings of SPIE - The International Society for Optical Engineering · 2000 An evolutionary programming (EP) technique was investigated to reduce the complexity of artificial neural network (ANN) models that predict the outcome of mammography-induced breast biopsy. By combining input variables consisting of mammography lesion desc ... Cite

Use of a constraint satisfaction neural network for breast cancer diagnosis and dynamic scenarios simulation

Journal Article Proceedings of SPIE - The International Society for Optical Engineering · January 1, 2000 A constraint satisfaction neural network (CSNN) has been developed for breast cancer diagnosis from mammographic and clinical findings. CSNN is a circuit network aiming to maximize the activation of its nodes given the constraints existing among them. The ... Cite

Application of a GRNN oracle to the intelligent combination of several breast cancer benign/malignant predictive paradigms

Journal Article Intelligent Engineering Systems Through Artificial Neural Networks · December 1, 1999 The General Regression Neural Network (GRNN) is well known to be an extremely effective prediction model in a wide variety of problems. It has been recently established that in many prediction problems, the results obtained by intelligently combining the o ... Cite

A neural network to predict symptomatic lung injury.

Journal Article Phys Med Biol · September 1999 A nonlinear neural network that simultaneously uses pre-radiotherapy (RT) biological and physical data was developed to predict symptomatic lung injury. The input data were pre-RT pulmonary function, three-dimensional treatment plan doses and demographics. ... Full text Link to item Cite

Application of artificial neural networks for diagnosis of breast cancer

Journal Article Proceedings of the 1999 Congress on Evolutionary Computation, CEC 1999 · January 1, 1999 We review four current projects pertaining to artificial neural network (ANN) models that merge radiologist-extracted findings to perform computer aided diagnosis (CADx) of breast cancer. These projects are: (1) prediction of breast lesion malignancy using ... Full text Cite

Effect of patient history data on the prediction of breast cancer from mammographic findings with artificial neural networks.

Journal Article Acad Radiol · January 1999 RATIONALE AND OBJECTIVES: The authors evaluated the contribution of medical history data to the prediction of breast cancer with artificial neural network (ANN) models based on mammographic findings. MATERIALS AND METHODS: Three ANNs were developed: The fi ... Full text Link to item Cite

Case-based reasoning as a computer aid to diagnosis

Journal Article Proceedings of SPIE - The International Society for Optical Engineering · January 1, 1999 A Case-Based Reasoning (CBR) system has been developed to predict the outcome of excisional biopsy from mammographic findings. CBR is implemented by comparing the current case to all previous cases and examining the outcomes for those previous cases that m ... Cite

Application of evolutionary programming and probabilistic neural networks to breast cancer diagnosis

Journal Article Proceedings of the International Joint Conference on Neural Networks · January 1, 1999 Two novel artificial neural network techniques, evolutionary programming (EP) and probabilistic neural networks (PNN), were applied to the problem of breast cancer diagnosis. The EP is a stochastic optimization technique with the ability to mutate both net ... Cite

Constraint Satisfaction Neural Network for medical diagnosis

Journal Article Proceedings of the International Joint Conference on Neural Networks · January 1, 1999 This objective of this study was to explore how a Constraint Satisfaction Neural Network (CSNN) can be used for medical diagnostic tasks. The study is based on a database of 500 patients who underwent breast biopsy at Duke University Medical Center due to ... Cite

Prediction of breast biopsy outcomes from mammographic findings

Journal Article COMPUTER-AIDED DIAGNOSIS IN MEDICAL IMAGING · January 1, 1999 Link to item Cite

Computer-aided diagnosis of breast cancer

Journal Article COMPUTER-AIDED DIAGNOSIS IN MEDICAL IMAGING · January 1, 1999 Link to item Cite

Predictive model for the diagnosis of intraabdominal abscess.

Journal Article Acad Radiol · July 1998 RATIONALE AND OBJECTIVES: The authors investigated the use of an artificial neural network (ANN) to aid in the diagnosis of intraabdominal abscess. MATERIALS AND METHODS: An ANN was constructed based on data from 140 patients who underwent abdominal and pe ... Full text Link to item Cite

QoS middleware for Internet multimedia streaming

Journal Article NEC Tech. J. (Japan) · 1998 In real-time multimedia streaming, some control mechanism to maintain the quality of service (QoS) in data transfer, which includes not only network-level QoS guarantee by resource reservation but also adaptive control by end hosts according to the network ... Cite

Self-organizing maps for analyzing mammographic findings

Journal Article IEEE International Conference on Neural Networks - Conference Proceedings · December 1, 1997 The purpose of this study is to analyze mammographic findings using self-organizing map artificial neural networks. Using two findings of patient age and mass margin extracted by radiologists, self-organizing maps were developed to analyze both the distrib ... Full text Cite

Predicting breast cancer invasion with artificial neural networks on the basis of mammographic features.

Journal Article Radiology · April 1997 PURPOSE: To evaluate whether an artificial neural network (ANN) can predict breast cancer invasion on the basis of readily available medical findings (ie, mammographic findings classified according to the American College of Radiology Breast Imaging Report ... Full text Link to item Cite

Computer-aided diagnosis of mammography using an artificial neural network: Predicting the invasiveness of breast cancers from image features

Journal Article Proceedings of SPIE - The International Society for Optical Engineering · December 1, 1996 The study aimed to develop an artificial neural network (ANN) for computer-aided diagnosis of mammography. Using 9 mammographic image features and patient age, the ANN predicted whether breast lesions were benign, invasive malignant, or noninvasive maligna ... Full text Cite

Diffuse nodular lung disease on chest radiographs: a pilot study of characterization by fractal dimension.

Journal Article AJR Am J Roentgenol · November 1996 OBJECTIVE: We present a computer-aided diagnostic technique for identifying nodular interstitial lung disease on chest radiographs. The fractal dimension was used as a numerical measure of image texture on digital chest radiographs to distinguish patients ... Full text Link to item Cite

Artificial neural network: improving the quality of breast biopsy recommendations.

Journal Article Radiology · January 1996 PURPOSE: To evaluate the performance and inter- and intraobserver variability of an artificial neural network (ANN) for predicting breast biopsy outcome. MATERIALS AND METHODS: Five radiologists described 60 mammographically detected lesions with the Ameri ... Full text Link to item Cite

Computer aided diagnosis in thoracic and mammographic radiology

Journal Article Med. Imaging Technol. (Japan) · 1996 There has been a significant effort in the radiology department at Duke University to develop computer aided diagnosis (CAD) systems. The goal of the development of these systems is to assist radiologists in interpreting radiographic images and findings. T ... Cite

Academic consortium for the evaluation of computer-aided diagnosis (CADx) in mammography

Journal Article Proceedings of SPIE - The International Society for Optical Engineering · December 1, 1995 Computer aided diagnosis (CADx) is a promising technology for the detection of breast cancer in screening mammography. A number of different approaches have been developed for CADx research that have achieved significant levels of performance. Research tea ... Cite

Computer-aided diagnosis of breast cancer: artificial neural network approach for optimized merging of mammographic features.

Journal Article Acad Radiol · October 1995 RATIONALE AND OBJECTIVES: An artificial neural network (ANN) approach was developed for the computer-aided diagnosis of mammography using an optimally minimized number of input features. METHODS: A backpropagation ANN merged nine input features (age plus e ... Full text Link to item Cite

Breast cancer: prediction with artificial neural network based on BI-RADS standardized lexicon.

Journal Article Radiology · September 1995 PURPOSE: To determine if an artificial neural network (ANN) to categorize benign and malignant breast lesions can be standardized for use by all radiologists. MATERIALS AND METHODS: An ANN was constructed based on the standardized lexicon of the Breast Ima ... Full text Link to item Cite

Computer-aided diagnosis of mammograms using an artificial neural network: Merging of standardized input features from the ACR lexicon

Journal Article Proceedings of SPIE - The International Society for Optical Engineering · May 12, 1995 This study aimed to develop an artificial neural network for computer-aided diagnosis in mammography, using an optimally minimized number of inputs from a standardized lexicon for mammographic features. A three-layer backpropagation neural network merged s ... Full text Cite

COMPUTER-AIDED DIAGNOSIS OF BREAST MASS MALIGNANCY WITH AUTOMATED FEATURE-EXTRACTION AND ARTIFICIAL NEURAL NETWORKS

Conference RADIOLOGY · 1995 Cite

Prediction of breast cancer malignancy using an artificial neural network.

Journal Article Cancer · December 1, 1994 BACKGROUND: An artificial neural network (ANN) was developed to predict breast cancer from mammographic findings. This network was evaluated in a retrospective study. METHODS: For a set of patients who were scheduled for biopsy, radiologists interpreted th ... Full text Link to item Cite

Bayesian restoration of chest radiographs. Scatter compensation with improved signal-to-noise ratio.

Journal Article Invest Radiol · October 1994 OBJECTIVES: The authors introduce a Bayesian algorithm for digital chest radiography that increases the signal-to-noise ratio, and thus detectability, for low-contrast objects. METHOD: The improved images are formed as a maximum a posteriori probability es ... Full text Link to item Cite

Spatially varying scatter compensation for chest radiographs using a hybrid Madaline artificial neural network

Journal Article Proceedings of SPIE - The International Society for Optical Engineering · May 11, 1994 We developed a hybrid artificial neural network for scatter compensation in digital portable chest radiographs. The network inputs an image region of interest (ROl), and outputs the scatter estimate at the ROl's center. We segmented each image into four re ... Full text Cite

Scatter compensation in digital chest radiography using the posterior beam stop technique.

Journal Article Med Phys · March 1994 A new scatter compensation technique for computed radiography based on posterior beam stop (PBS) sampled scatter measurements and the bicubic spline interpolation technique was proposed. Using only a single exposure, both the clinical image and an array of ... Full text Link to item Cite

PREDICTION OF BREAST-CANCER MALIGNANCY FOR DIFFICULT CASES USING AN ARTIFICIAL NEURAL-NETWORK

Conference WORLD CONGRESS ON NEURAL NETWORKS-SAN DIEGO - 1994 INTERNATIONAL NEURAL NETWORK SOCIETY ANNUAL MEETING, VOL 1 · January 1, 1994 Link to item Cite

Observer evaluation of scatter subtraction for digital portable chest radiographs.

Journal Article Invest Radiol · August 1993 RATIONALE AND OBJECTIVES: The authors compared standard digital portable chest radiographs (DPCXR) to scatter-subtracted DPCXR: METHODS: Thirty DPCXR were obtained using a photostimulable phosphor digital imaging system and a posterior beam stop (PBS) tech ... Full text Link to item Cite

Measurement of scatter fractions in erect posteroanterior and lateral chest radiography.

Journal Article Radiology · July 1993 Scatter fractions (SFs) measured in patients undergoing erect posteroanterior (PA) and lateral chest radiography with a 12:1 antiscatter grid are reported. Modifications to the posterior beam-stop (PBS) technique allowed measurement of scatter in these pat ... Full text Link to item Cite

Scatter compensation for digital chest radiography using maximum likelihood expectation maximization.

Journal Article Invest Radiol · May 1993 RATIONALE AND OBJECTIVES: An iterative maximum likelihood expectation maximization algorithm (MLEM) has been developed for scatter compensation in chest radiography. METHODS: The MLEM technique produces a scatter-reduced image which maximizes the probabili ... Full text Link to item Cite

An artificial neural network for estimating scatter exposures in portable chest radiography.

Journal Article Med Phys · 1993 An adaptive linear element (Adaline) was developed to estimate the two-dimensional scatter exposure distribution in digital portable chest radiographs (DPCXR). DPCXRs and quantitative scatter exposure measurements at 64 locations throughout the chest were ... Full text Link to item Cite

SCATTER REDUCTION IN PORTABLE DIGITAL CHEST RADIOGRAPHY WITH BAYESIAN IMAGE ESTIMATION

Journal Article RADIOLOGY · November 1, 1992 Link to item Cite

SPATIALLY VARYING SCATTER ESTIMATION IN PORTABLE CHEST RADIOGRAPHY WITH AN ARTIFICIAL NEURAL NETWORK

Journal Article RADIOLOGY · November 1, 1992 Link to item Cite

Measurement of scatter fractions in clinical bedside radiography.

Journal Article Radiology · June 1992 The authors present measurements of scatter fraction (SF), the ratio of scattered to total imaged photons, from clinical bedside radiographs of 102 patients. These measurements were obtained by using a new posterior beam-stop technique that does not alter ... Full text Link to item Cite

Posterior beam-stop method for scatter fraction measurement in digital radiography.

Journal Article Invest Radiol · February 1992 The authors presented a new posterior beam-stop (PBS) technique for measuring the ratio of scattered to total-detected photon flux (scatter fraction) in a radiographic examination while preserving the diagnostic quality of the image. The scatter measuremen ... Full text Link to item Cite

Quantitative scatter measurement in digital radiography using a photostimulable phosphor imaging system.

Journal Article Med Phys · 1991 X-ray scatter fractions measured with two detectors are compared: a photostimulable phosphor system (PSP) and a conventional film-screen technique. For both detection methods, a beam-stop technique was used to estimate the scatter fraction in polystyrene p ... Full text Link to item Cite

Scatter fractions in AMBER imaging.

Journal Article Radiology · December 1990 Images of two phantoms were obtained with use of an advanced multiple-beam equalization radiography system, and scatter fractions were estimated with use of a photostimulable phosphor imaging system. Scatter fractions in the equalized images were lower in ... Full text Link to item Cite

Artificial neural networks for SPECT image reconstruction with optimized weighted backprojection

Conference Conference Record of the 1991 IEEE Nuclear Science Symposium and Medical Imaging Conference Full text Cite