Scholars@Duke
Lars Johannes L Grimm

Lars Johannes L Grimm

Associate Professor of Radiology
Radiology, Breast Imaging
lars.grimm@duke.edu
Dept of Radiology, Box 3808, Durham, NC 27710

Scholarly Works - Conferences

MammoTracker: Mask-Guided Lesion Tracking in Temporal Mammograms

Conference Lecture Notes in Computer Science · January 1, 2026 Accurate lesion tracking in temporal mammograms is essential for monitoring breast cancer progression and facilitating early diagnosis. However, automated lesion correspondence across exams remains a challenges in computer-aided diagnosis (CAD) systems, li ... Full text Cite

BreastSegNet: Multi-label Segmentation of Breast MRI

Conference Lecture Notes in Computer Science · January 1, 2026 Breast MRI provides high-resolution imaging critical for breast cancer screening and preoperative staging. However, existing segmentation methods for breast MRI remain limited in scope, often focusing on only a few anatomical structures, such as fibrogland ... Full text Cite

Longitudinal Mammogram Exam-Based Breast Cancer Diagnosis Models: Vulnerability to Adversarial Attacks

Conference Lecture Notes in Computer Science · January 1, 2026 In breast cancer detection and diagnosis, the longitudinal analysis of mammogram images is crucial. Contemporary models excel in detecting temporal imaging feature changes, thus enhancing the learning process over sequential imaging exams. Yet, the resilie ... Full text Cite

Abstract GS2-05: Early Oncologic Outcomes Following Active Monitoring or Surgery (+/- Radiation) for Low Risk DCIS: the Comparing an Operation to Monitoring, with or without Endocrine Therapy (COMET) Study (AFT-25)

Conference Clinical Cancer Research · June 13, 2025 AbstractBackground: Over 50,000 women in the United States will be diagnosed with ductal carcinoma in situ (DCIS) this year alone. Almost all of these diagnoses will be made in completely asymptomatic indivi ... Full text Cite

Abstract 7482: Mapping the temporal landscape of breast cancer using epigenetic entropy

Conference Cancer Research · April 21, 2025 AbstractBackground:The age of a newly diagnosed breast cancer encodes valuable etiologic and prognostic information, yet it is conside ... Full text Cite

The Influence of Extracurricular Activities on Radiology Resident Selection Decisions.

Conference J Am Coll Radiol · June 2024 PURPOSE: Extracurricular activities (EAs) listed on radiology residency applications can signal traits and characteristics desired in holistic reviews. The authors conducted an objective analysis to determine the influence of EAs on resident selection deci ... Full text Link to item Cite

Abstract PO4-13-04: Added Value from Patient Advocates in a Translational Working Group: the COMET Study

Conference Cancer Research · May 2, 2024 AbstractIntroduction: A phase III multicenter prospective randomized clinical trial called “Comparing an Operation to Monitoring, with or without Endocrine Therapy (COMET)” (NCT02926911) assesses the risks/b ... Full text 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

From the lab to the clinic: Lessons learned from a translational working group.

Conference Journal of Clinical Oncology · June 1, 2023 e12576 Background: Comparing an Operation to Monitoring, with or without Endocrine Therapy (COMET), is a phase III multicenter prospective randomized clinical trial comparing the risks/benefits of active monitoring (AM) versus su ... Full text Cite

Abstract P6-04-13: Centralized adequacy assessment of ductal carcinoma in situ samples for the COMET study (AFT-25)

Conference Cancer Research · March 1, 2023 AbstractIntroduction COMET (Comparing an Operation to Monitoring, with or without Endocrine Therapy) is a phase III clinical trial randomizing patients diagnosed with low-intermediate grade DCIS to either ac ... Full text 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

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

Disparities in surveillance imaging after breast conserving surgery for primary DCIS.

Conference Journal of Clinical Oncology · May 20, 2021 6516 Background: Due to the elevated risk of ipsilateral invasive breast cancer (iIBC) after diagnosis with primary ductal carcinoma in situ (DCIS), professional guidelines recommend surveillance screening within 6-12 months (mo) ... 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

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

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

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

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

It’s Not You, It’s Me: The Influence of Surgeon Gender on Patient Satisfaction Scores

Conference Journal of the American College of Surgeons · October 2018 Full text Cite

Abstract LB-302: Oncolytic poliovirus-mediated inflammation and immunity in breast cancer

Conference Cancer Research · July 1, 2018 AbstractBreast cancer is the most common malignancy among women in the United States and the second leading cause of cancer deaths in women. Disease prognosis, local recurrence rates and response to therapy ... Full text Cite

Convolutional encoder-decoder for breast mass segmentation in digital breast tomosynthesis

Conference Progress in Biomedical Optics and Imaging Proceedings of SPIE · January 1, 2018 Digital breast tomosynthesis (DBT) is a relatively new modality for breast imaging that can provide detailed assessment of dense tissue within the breast. In the domains of cancer diagnosis, radiogenomics, and resident education, it is important to accurat ... Full text Cite

Association of high proliferation marker Ki-67 expression with DCEMR imaging features of breast: A large scale evaluation

Conference Progress in Biomedical Optics and Imaging Proceedings of SPIE · January 1, 2018 One of the methods widely used to measure the proliferative activity of cells in breast cancer patients is the immunohistochemical (IHC) measurement of the percentage of cells stained for nuclear antigen Ki-67. Use of Ki-67 expression as a prognostic marke ... Full text 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

Deep learning-based features of breast MRI for prediction of occult invasive disease following a diagnosis of ductal carcinoma in situ: Preliminary data

Conference Progress in Biomedical Optics and Imaging Proceedings of SPIE · January 1, 2018 Approximately 25% of patients with ductal carcinoma in situ (DCIS) diagnosed from core needle biopsy are subsequently upstaged to invasive cancer at surgical excision. Identifying patients with occult invasive disease is important as it changes treatment a ... 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

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

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

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