[HTML][HTML] Artificial Intelligence for context-aware surgical guidance in complex robot-assisted oncological procedures: An exploratory feasibility study

FR Kolbinger, S Bodenstedt, M Carstens… - European Journal of …, 2023 - Elsevier
Introduction Complex oncological procedures pose various surgical challenges including
dissection in distinct tissue planes and preservation of vulnerable anatomical structures …

Self-supervised learning for endoscopic video analysis

R Hirsch, M Caron, R Cohen, A Livne… - … Conference on Medical …, 2023 - Springer
Self-supervised learning (SSL) has led to important breakthroughs in computer vision by
allowing learning from large amounts of unlabeled data. As such, it might have a pivotal role …

Encoding surgical videos as latent spatiotemporal graphs for object and anatomy-driven reasoning

A Murali, D Alapatt, P Mascagni, A Vardazaryan… - … Conference on Medical …, 2023 - Springer
Recently, spatiotemporal graphs have emerged as a concise and elegant manner of
representing video clips in an object-centric fashion, and have shown to be useful for …

Latent graph representations for critical view of safety assessment

A Murali, D Alapatt, P Mascagni… - … on Medical Imaging, 2023 - ieeexplore.ieee.org
Assessing the critical view of safety in laparoscopic cholecystectomy requires accurate
identification and localization of key anatomical structures, reasoning about their geometric …

SSL-CPCD: Self-supervised learning with composite pretext-class discrimination for improved generalisability in endoscopic image analysis

Z Xu, J Rittscher, S Ali - IEEE Transactions on Medical Imaging, 2024 - ieeexplore.ieee.org
Data-driven methods have shown tremendous progress in medical image analysis. In this
context, deep learning-based supervised methods are widely popular. However, they …

The endoscapes dataset for surgical scene segmentation, object detection, and critical view of safety assessment: official splits and benchmark

A Murali, D Alapatt, P Mascagni, A Vardazaryan… - arXiv preprint arXiv …, 2023 - arxiv.org
This technical report provides a detailed overview of Endoscapes, a dataset of laparoscopic
cholecystectomy (LC) videos with highly intricate annotations targeted at automated …

Cyclesam: One-shot surgical scene segmentation using cycle-consistent feature matching to prompt sam

A Murali, P Mascagni, D Mutter, N Padoy - arXiv preprint arXiv:2407.06795, 2024 - arxiv.org
The recently introduced Segment-Anything Model (SAM) has the potential to greatly
accelerate the development of segmentation models. However, directly applying SAM to …

A Study on Self-Supervised Pretraining for Vision Problems in Gastrointestinal Endoscopy

E Sanderson, BJ Matuszewski - IEEE Access, 2024 - ieeexplore.ieee.org
Solutions to vision tasks in gastrointestinal endoscopy (GIE) conventionally use image
encoders pretrained in a supervised manner with ImageNet-1k as backbones. However, the …

Live laparoscopic video retrieval with compressed uncertainty

T Yu, P Mascagni, J Verde, J Marescaux, D Mutter… - Medical Image …, 2023 - Elsevier
Searching through large volumes of medical data to retrieve relevant information is a
challenging yet crucial task for clinical care. However the primitive and most common …

Learning multi-modal representations by watching hundreds of surgical video lectures

K Yuan, V Srivastav, T Yu, J Lavanchy, P Mascagni… - 2023 - hal.science
Recent advancements in surgical computer vision applications have been driven by fully-
supervised methods, primarily using only visual data. These methods rely on manually …