output
20162026
most citedSurgical Data Science: Enabling Next-Generation Surgery

578 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions
Showing 2025 · cs.CVShow all

4 papers · 2 filters

cs.CV2025

Endoshare: A Publicly Available, Surgeons-Friendly Solution to De-Identify and Manage Surgical Videos

Lorenzo Arboit, Dennis N. Schneider, Britty Baby +3

Video-based assessment and surgical data science can advance surgical training, research, and quality improvement, yet adoption remains limited by heterogeneous recording formats a…

cs.CV2025

Federated Learning for Surgical Vision in Appendicitis Classification: Results of the FedSurg EndoVis 2024 Challenge

Max Kirchner, Hanna Hoffmann, Alexander C. Jenke +16

Developing generalizable surgical AI requires multi-institutional data, yet privacy constraints preclude direct data sharing, making Federated Learning (FL) a natural candidate. It…

cs.CV2025

S4M: 4-points to Segment Anything

Adrien Meyer, Lorenzo Arboit, Giuseppe Massimiani +3

Purpose: The Segment Anything Model (SAM) promises to ease the annotation bottleneck in medical segmentation, but overlapping anatomy and blurred boundaries make its point prompts…

cs.CV2025★ 6 cited

Early Operative Difficulty Assessment in Laparoscopic Cholecystectomy via Snapshot-Centric Video Analysis

Saurav Sharma, Maria Vannucci, Leonardo Pestana Legori +6

Purpose: Laparoscopic cholecystectomy (LC) operative difficulty (LCOD) is highly variable and influences outcomes. Despite extensive LC studies in surgical workflow analysis, limit…