210 citations · 1.2k across the 63 of their papers we have counts for
12 papers · 1 filter
ST(OR)2: Spatio-Temporal Object Level Reasoning for Activity Recognition in the Operating Room
Idris Hamoud, Muhammad Abdullah Jamal, Vinkle Srivastav +3
Surgical robotics holds much promise for improving patient safety and clinician experience in the Operating Room (OR). However, it also comes with new challenges, requiring strong…
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…
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…
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…
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…
Jumpstarting Surgical Computer Vision
Deepak Alapatt, Aditya Murali, Vinkle Srivastav +3
Consensus amongst researchers and industry points to a lack of large, representative annotated datasets as the biggest obstacle to progress in the field of surgical data science. A…
Surgical Action Triplet Detection by Mixed Supervised Learning of Instrument-Tissue Interactions
Saurav Sharma, Chinedu Innocent Nwoye, Didier Mutter +1
Surgical action triplets describe instrument-tissue interactions as (instrument, verb, target) combinations, thereby supporting a detailed analysis of surgical scene activities and…
Why is the winner the best?
Matthias Eisenmann, Annika Reinke, Vivienn Weru +122
International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to in…
Self-distillation for surgical action recognition
Amine Yamlahi, Thuy Nuong Tran, Patrick Godau +9
Surgical scene understanding is a key prerequisite for contextaware decision support in the operating room. While deep learning-based approaches have already reached or even surpas…
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…
CholecTriplet2022: Show me a tool and tell me the triplet -- an endoscopic vision challenge for surgical action triplet detection
Chinedu Innocent Nwoye, Tong Yu, Saurav Sharma +46
Formalizing surgical activities as triplets of the used instruments, actions performed, and target anatomies is becoming a gold standard approach for surgical activity modeling. Th…
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…