42 citations · 103 across the 10 of their papers we have counts for
10 papers
Optimizing Human-Machine Interface for Real-Time AI Support in the Operating Room: the CVS Copilot
Lorenzo Arboit, Nicolas Chanel, Aditya Murali +2
Artificial intelligence (AI) systems for automated Critical View of Safety (CVS) assessment in laparoscopic cholecystectomy are nearing clinical translation. Beyond algorithmic per…
UltraSam: A Foundation Model for Ultrasound using Large Open-Access Segmentation Datasets
Adrien Meyer, Aditya Murali, Farahdiba Zarin +2
Purpose: Automated ultrasound image analysis is challenging due to anatomical complexity and limited annotated data. To tackle this, we take a data-centric approach, assembling the…
CycleSAM: Few-Shot Surgical Scene Segmentation with Cycle- and Scene-Consistent Feature Matching
Aditya Murali, Farahdiba Zarin, Adrien Meyer +3
Surgical image segmentation is highly challenging, primarily due to scarcity of annotated data. Generalist prompted segmentation models like the Segment-Anything Model (SAM) can he…
Optimizing Latent Graph Representations of Surgical Scenes for Zero-Shot Domain Transfer
Siddhant Satyanaik, Aditya Murali, Deepak Alapatt +3
Purpose: Advances in deep learning have resulted in effective models for surgical video analysis; however, these models often fail to generalize across medical centers due to domai…
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…
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…
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…
Latent Graph Representations for Critical View of Safety Assessment
Aditya Murali, Deepak Alapatt, Pietro Mascagni +5
Assessing the critical view of safety in laparoscopic cholecystectomy requires accurate identification and localization of key anatomical structures, reasoning about their geometri…
Dissecting Self-Supervised Learning Methods for Surgical Computer Vision
Sanat Ramesh, Vinkle Srivastav, Deepak Alapatt +10
The field of surgical computer vision has undergone considerable breakthroughs in recent years with the rising popularity of deep neural network-based methods. However, standard fu…