23 citations · 44 across the 12 of their papers we have counts for
12 papers
SPIRIT: Spatio-temporal Pairwise Relational Modeling of Instrument-Tissue Interactions for Surgical Action Triplet Recognition
Saurav Sharma, Lorenzo Arboit, Nabani Banik +11
Fine-grained understanding of surgical activity is essential for context-aware assistance in the operating room, including safety monitoring, adverse event identification, and skil…
Multimodal Assessment of Pancreatic Cancer Resectability Using Deep Learning
Vincent Ochs, Christoph Kuemmerli, Florentin Bieder +12
Accurate determination of pancreatic ductal adenocarcinoma (PDAC) resectability relies on evaluating how the tumor interacts with major peripancreatic vessels on CT imaging, yet ex…
Current validation practice undermines surgical AI development
Annika Reinke, Ziying O. Li, Minu D. Tizabi +98
Surgical data science (SDS) is rapidly advancing, yet clinical adoption of artificial intelligence (AI) in surgery remains limited, with inadequate validation as an important contr…
Leveraging Generic Foundation Models for Multimodal Surgical Data Analysis
Simon Pezold, Jérôme A. Kurylec, Jan S. Liechti +2
We investigate how both the adaptation of a generic foundation model via transfer learning and the integration of complementary modalities from the operating room (OR) can support…
Recognizing Surgical Phases Anywhere: Few-Shot Test-time Adaptation and Task-graph Guided Refinement
Kun Yuan, Tingxuan Chen, Shi Li +9
The complexity and diversity of surgical workflows, driven by heterogeneous operating room settings, institutional protocols, and anatomical variability, present a significant chal…
When do they StOP?: A First Step Towards Automatically Identifying Team Communication in the Operating Room
Keqi Chen, Lilien Schewski, Vinkle Srivastav +5
Purpose: Surgical performance depends not only on surgeons' technical skills but also on team communication within and across the different professional groups present during the o…
Surgical Text-to-Image Generation
Chinedu Innocent Nwoye, Rupak Bose, Kareem Elgohary +5
Acquiring surgical data for research and development is significantly hindered by high annotation costs and practical and ethical constraints. Utilizing synthetically generated ima…
Challenges in Multi-centric Generalization: Phase and Step Recognition in Roux-en-Y Gastric Bypass Surgery
Joel L. Lavanchy, Sanat Ramesh, Diego Dall'Alba +7
Most studies on surgical activity recognition utilizing Artificial intelligence (AI) have focused mainly on recognizing one type of activity from small and mono-centric surgical vi…
Advancing Surgical VQA with Scene Graph Knowledge
Kun Yuan, Manasi Kattel, Joel L. Lavanchy +3
Modern operating room is becoming increasingly complex, requiring innovative intra-operative support systems. While the focus of surgical data science has largely been on video ana…
CholecTrack20: A Multi-Perspective Tracking Dataset for Surgical Tools
Chinedu Innocent Nwoye, Kareem Elgohary, Anvita Srinivas +3
Tool tracking in surgical videos is essential for advancing computer-assisted interventions, such as skill assessment, safety zone estimation, and human-machine collaboration. Howe…
Learning Multi-modal Representations by Watching Hundreds of Surgical Video Lectures
Kun Yuan, Vinkle Srivastav, Tong Yu +5
Recent advancements in surgical computer vision applications have been driven by vision-only models, which do not explicitly integrate the rich semantics of language into their des…
Preserving Privacy in Surgical Video Analysis Using Artificial Intelligence: A Deep Learning Classifier to Identify Out-of-Body Scenes in Endoscopic Videos
Joël L. Lavanchy, Armine Vardazaryan, Pietro Mascagni +3
Objective: To develop and validate a deep learning model for the identification of out-of-body images in endoscopic videos. Background: Surgical video analysis facilitates educatio…