activity
20182026
most citedSurgical data science for safe cholecystectomy: a protocol for segmentation of hepatocystic anatomy and assessment of the critical view of safety

9 citations · 15 across the 5 of their papers we have counts for

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5 papers · 1 filter

cs.CV2026

Self-Supervised Uncalibrated Multi-View Video Anonymization in the Operating Room

Keqi Chen, Vinkle Srivastav, Armine Vardazaryan +3

Privacy preservation is a prerequisite for using video data in Operating Room (OR) research. Effective anonymization relies on the exhaustive localization of every individual; even…

cs.CV2025

Learning from Sparse Point Labels for Dense Carcinosis Localization in Advanced Ovarian Cancer Assessment

Farahdiba Zarin, Riccardo Oliva, Vinkle Srivastav +7

Learning from sparse labels is a challenge commonplace in the medical domain. This is due to numerous factors, such as annotation cost, and is especially true for newly introduced…

cs.CV2023

Encoding Surgical Videos as Latent Spatiotemporal Graphs for Object and Anatomy-Driven Reasoning

Aditya Murali, Deepak Alapatt, Pietro Mascagni +5

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 downstream ta…

cs.CV2023

The Endoscapes Dataset for Surgical Scene Segmentation, Object Detection, and Critical View of Safety Assessment: Official Splits and Benchmark

Aditya Murali, Deepak Alapatt, Pietro Mascagni +8

This technical report provides a detailed overview of Endoscapes, a dataset of laparoscopic cholecystectomy (LC) videos with highly intricate annotations targeted at automated asse…

cs.CV2018

Weakly-Supervised Learning for Tool Localization in Laparoscopic Videos

Armine Vardazaryan, Didier Mutter, Jacques Marescaux +1

Surgical tool localization is an essential task for the automatic analysis of endoscopic videos. In the literature, existing methods for tool localization, tracking and segmentatio…