output
20042025
most citedThe Liver Tumor Segmentation Benchmark (LiTS)

1.2k 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 2023Show all

6 papers · 1 filter

cs.CV2023★ 16 cited

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★ 24 cited

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.AI2023

Automated Driving Without Ethics: Meaning, Design and Real-World Implementation

Katherine Evans, Nelson de Moura, Raja Chatila +1

The ethics of automated vehicles (AV) has received a great amount of attention in recent years, specifically in regard to their decisional policies in accident situations in which…

cs.CV2023★ 9 cited

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…

cs.CV2023★ 14 cited

Weakly Supervised Temporal Convolutional Networks for Fine-grained Surgical Activity Recognition

Sanat Ramesh, Diego Dall'Alba, Cristians Gonzalez +6

Automatic recognition of fine-grained surgical activities, called steps, is a challenging but crucial task for intelligent intra-operative computer assistance. The development of c…

cs.CV2023★ 23 cited

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…