Guy Rosman

Journal article IEEE Robotics and Automation Letters · January 1, 2025 We provide a sober look at the application of Multimodal Large Language Models (MLLMs) in autonomous driving, challenging common assumptions about their ability to interpret dynamic driving scenarios. Despite advances in models like GPT-4o, their performan ... Full text Cite

Personalizing driver safety interfaces via driver cognitive factors inference.

Journal article Sci Rep · August 5, 2024 Recent advances in AI and intelligent vehicle technology hold the promise of revolutionizing mobility and transportation through advanced driver assistance systems (ADAS). Certain cognitive factors, such as impulsivity and inhibitory control have been show ... Full text Link to item Cite

Concept Graph Neural Networks for Surgical Video Understanding.

Journal article IEEE Trans Med Imaging · January 2024 Analysis of relations between objects and comprehension of abstract concepts in the surgical video is important in AI-augmented surgery. However, building models that integrate our knowledge and understanding of surgery remains a challenging endeavor. In t ... Full text Link to item Cite

SAGES consensus recommendations on surgical video data use, structure, and exploration (for research in artificial intelligence, clinical quality improvement, and surgical education).

Journal article Surg Endosc · November 2023 BACKGROUND: Surgery generates a vast amount of data from each procedure. Particularly video data provides significant value for surgical research, clinical outcome assessment, quality control, and education. The data lifecycle is influenced by various fact ... Full text Link to item Cite

Multi-Abstractive Neural Controller: An Efficient Hierarchical Control Architecture for Interactive Driving

Journal article IEEE Robotics and Automation Letters · August 1, 2023 As learning-based methods make their way from perception systems to planning/control stacks, robot control systems have started to enjoy the benefits that data-driven methods provide. Because control systems directly affect the motion of the robot, data-dr ... Full text Cite

TEsoNet: knowledge transfer in surgical phase recognition from laparoscopic sleeve gastrectomy to the laparoscopic part of Ivor-Lewis esophagectomy.

Journal article Surg Endosc · May 2023 BACKGROUND: Surgical phase recognition using computer vision presents an essential requirement for artificial intelligence-assisted analysis of surgical workflow. Its performance is heavily dependent on large amounts of annotated video data, which remain a ... Full text Link to item Cite

Artificial intelligence prediction of cholecystectomy operative course from automated identification of gallbladder inflammation.

Journal article Surg Endosc · September 2022 BACKGROUND: Operative courses of laparoscopic cholecystectomies vary widely due to differing pathologies. Efforts to assess intra-operative difficulty include the Parkland grading scale (PGS), which scores inflammation from the initial view of the gallblad ... Full text Link to item Cite

SUPR-GAN: SUrgical PRediction GAN for Event Anticipation in Laparoscopic and Robotic Surgery

Journal article IEEE Robotics and Automation Letters · April 1, 2022 Comprehension of surgical workflow is the foundation upon which artificial intelligence (AI) and machine learning (ML) holds the potential to assist intraoperative decision making and risk mitigation. In this work, we move beyond mere identification of pas ... Full text Cite

Learning an Explainable Trajectory Generator Using the Automaton Generative Network (AGN)

Journal article IEEE Robotics and Automation Letters · April 1, 2022 Symbolic reasoning is a key component for enabling practical use of data-driven planners in autonomous driving. In that context, deterministic finite state automata (DFA) are often used to formalize the underlying high-level decision-making process. Manual ... Full text Cite

Challenges in surgical video annotation.

Journal article Comput Assist Surg (Abingdon) · December 2021 Annotation of surgical video is important for establishing ground truth in surgical data science endeavors that involve computer vision. With the growth of the field over the last decade, several challenges have been identified in annotating spatial, tempo ... Full text Link to item Cite

SAGES consensus recommendations on an annotation framework for surgical video.

Journal article Surg Endosc · September 2021 BACKGROUND: The growing interest in analysis of surgical video through machine learning has led to increased research efforts; however, common methods of annotating video data are lacking. There is a need to establish recommendations on the annotation of s ... Full text Link to item Cite

Automated operative phase identification in peroral endoscopic myotomy.

Journal article Surg Endosc · July 2021 BACKGROUND: Artificial intelligence (AI) and computer vision (CV) have revolutionized image analysis. In surgery, CV applications have focused on surgical phase identification in laparoscopic videos. We proposed to apply CV techniques to identify phases in ... Full text Link to item Cite

CARPAL: Confidence-Aware Intent Recognition for Parallel Autonomy

Journal article IEEE Robotics and Automation Letters · July 1, 2021 Predicting driver intentions is a difficult and crucial task for advanced driver assistance systems. Traditional confidence measures on predictions often ignore the way predicted trajectories affect downstream decisions for safe driving. In this letter, we ... Full text Cite

Computer vision in surgery.

Journal article Surgery · May 2021 The fields of computer vision (CV) and artificial intelligence (AI) have undergone rapid advancements in the past decade, many of which have been applied to the analysis of intraoperative video. These advances are driven by wide-spread application of deep ... Full text Link to item Cite

Vehicle Trajectory Prediction Using Generative Adversarial Network with Temporal Logic Syntax Tree Features

Journal article IEEE Robotics and Automation Letters · April 1, 2021 In this work, we propose a novel approach for integrating rules into traffic agent trajectory prediction. Consideration of rules is important for understanding how people behave-yet, it cannot be assumed that rules are always followed. To address this chal ... Full text Cite

Deep Context Maps: Agent Trajectory Prediction Using Location-Specific Latent Maps

Journal article IEEE Robotics and Automation Letters · October 1, 2020 In this letter, we propose a novel approach for agent motion prediction in cluttered environments. One of the main challenges in predicting agent motion is accounting for location and context-specific information. Our main contribution is the concept of le ... Full text Cite

DiversityGAN: Diversity-Aware Vehicle Motion Prediction via Latent Semantic Sampling

Journal article IEEE Robotics and Automation Letters · October 1, 2020 Vehicle trajectory prediction is crucial for autonomous driving and advanced driver assistant systems. While existing approaches may sample from a predicted distribution of vehicle trajectories, they lack the ability to explore it-a key ability for evaluat ... Full text Cite

Artificial Intelligence in Anesthesiology: Current Techniques, Clinical Applications, and Limitations.

Journal article Anesthesiology · February 2020 Artificial intelligence has been advancing in fields including anesthesiology. This scoping review of the intersection of artificial intelligence and anesthesia research identified and summarized six themes of applications of artificial intelligence in ane ... Full text Link to item Cite

Probabilistic Risk Metrics for Navigating Occluded Intersections

Journal article IEEE Robotics and Automation Letters · October 1, 2019 Among traffic accidents in the USA, 23% of fatal and 32% of non-fatal incidents occurred at intersections. For driver assistance systems, intersection navigation remains a difficult problem that is critically important to increasing driver safety. In this ... Full text Cite

Computer Vision Analysis of Intraoperative Video: Automated Recognition of Operative Steps in Laparoscopic Sleeve Gastrectomy.

Journal article Ann Surg · September 2019 OBJECTIVE(S): To develop and assess AI algorithms to identify operative steps in laparoscopic sleeve gastrectomy (LSG). BACKGROUND: Computer vision, a form of artificial intelligence (AI), allows for quantitative analysis of video by computers for identifi ... Full text Link to item Cite

Response to Comment on "Artificial Intelligence in Surgery Requires Interdisciplinary Collaboration and Understanding".

Journal article Ann Surg · June 2019 Full text Link to item Cite

Surgical Video in the Age of Big Data.

Journal article Ann Surg · December 2018 Full text Link to item Cite

Information-Driven Adaptive Structured-Light Scanners

Journal article IEEE Transactions on Computational Imaging · September 2018 Full text Cite

Artificial Intelligence in Surgery: Promises and Perils.

Journal article Ann Surg · July 2018 OBJECTIVE: The aim of this review was to summarize major topics in artificial intelligence (AI), including their applications and limitations in surgery. This paper reviews the key capabilities of AI to help surgeons understand and critically evaluate new ... Full text Link to item Cite

The Manhattan Frame Model-Manhattan World Inference in the Space of Surface Normals.

Journal article IEEE Trans Pattern Anal Mach Intell · January 2018 Objects and structures within man-made environments typically exhibit a high degree of organization in the form of orthogonal and parallel planes. Traditional approaches utilize these regularities via the restrictive, and rather local, Manhattan World (MW) ... Full text Link to item Cite

Multi-Region Active Contours with a Single Level Set Function.

Journal article IEEE Trans Pattern Anal Mach Intell · August 2015 Segmenting an image into an arbitrary number of coherent regions is at the core of image understanding. Many formulations of the segmentation problem have been suggested over the past years. These formulations include, among others, axiomatic functionals, ... Full text Link to item Cite

Patch-collaborative spectral point-cloud denoising

Journal article Computer Graphics Forum · January 1, 2013 We present a new framework for point cloud denoising by patch-collaborative spectral analysis. A collaborative generalization of each surface patch is defined, combining similar patches from the denoised surface. The Laplace-Beltrami operator of the collab ... Full text Cite

On semi-implicit splitting schemes for the beltrami color image filtering

Journal article Journal of Mathematical Imaging and Vision · June 1, 2011 The Beltrami flow is an efficient nonlinear filter, that was shown to be effective for color image processing. The corresponding anisotropic diffusion operator strongly couples the spectral components. Usually, this flow is implemented by explicit schemes, ... Full text Cite

Nonlinear dimensionality reduction by topologically constrained isometric embedding

Journal article International Journal of Computer Vision · August 1, 2010 Many manifold learning procedures try to embed a given feature data into a flat space of low dimensionality while preserving as much as possible the metric in the natural feature space. The embedding process usually relies on distances between neighboring ... Full text Cite

Efficient Beltrami image filtering via vector extrapolation methods

Journal article SIAM Journal on Imaging Sciences · January 1, 2009 The Beltrami image flow is an effective nonlinear filter, often used in color image processing. It was shown to be closely related to the median, total variation, and bilateral filters. It treats the image as a two-dimensional manifold embedded in a hybrid ... Full text Cite