24 citations · 79 across the 19 of their papers we have counts for
21 papers
A Surgical Foundation Model Reveals Task-Dependent Label Efficiency
Florian Philipp Stilz, Lorenzo Arboit, Vinkle Srivastav +6
Developing label-efficient models is a central challenge in surgical AI due to the high cost and scarcity of expert annotation. While self-supervised foundation models adapt well t…
Artificial Intelligence for Workflow Analysis in Colorectal Surgery: A Multicentric, Cross-Procedural Development and Generalization Study
Pietro Mascagni, Julia Alekseenko, Pooja P Jain +10
Minimally invasive colorectal surgeries (MIS-CRS) are characterised by significant variability and inconsistent outcomes. ColoWorkflow, a tool for the video-based assessment (VBA)…
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…
GEN-Guard: Correcting Generalization Failures for Deployable Federated Surgical AI
Julia Alekseenko, Pietro Mascagni, AI4SafeChole Consortium +1
Federated Learning (FL) in surgical video AI enables collaborative model training without sharing sensitive data. However, standard evaluation practices - selecting the "best" glob…
AI for Quality Assurance in the Operating Room
Pietro Mascagni, Lalith Sharan, Deepak Alapatt +1
Surgical outcomes depend not only on patient factors and postoperative care but are also strongly influenced by the quality of the operation itself. Yet, for much of mod-ern surger…
SurgTEMP: Temporal-Aware Surgical Video Question Answering with Text-guided Visual Memory for Laparoscopic Cholecystectomy
Shi Li, Vinkle Srivastav, Shih-Min Yin +7
Surgical procedures are inherently complex and risky, requiring extensive expertise and constant focus to navigate evolving intraoperative scenes. Computer-assisted systems such as…
Artificial Intelligence for the Assessment of Peritoneal Carcinosis during Diagnostic Laparoscopy for Advanced Ovarian Cancer
Riccardo Oliva, Farahdiba Zarin, Alice Zampolini Faustini +9
Advanced Ovarian Cancer (AOC) is often diagnosed at an advanced stage with peritoneal carcinosis (PC). Fagotti score (FS) assessment at diagnostic laparoscopy (DL) guides treatment…
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…
Expert Consensus-based Video-Based Assessment Tool for Workflow Analysis in Minimally Invasive Colorectal Surgery: Development and Validation of ColoWorkflow
Pooja P Jain, Pietro Mascagni, Giuseppe Massimiani +14
Minimally invasive colorectal surgery is characterized by procedural variability, a difficult learning curve, and complications that impact quality and outcomes. Video-based assess…
The SAGES Critical View of Safety Challenge: A Global Benchmark for AI-Assisted Surgical Quality Assessment
Deepak Alapatt, Jennifer Eckhoff, Zhiliang Lyu +38
Advances in artificial intelligence (AI) for surgical quality assessment promise to democratize access to expertise, with applications in training, guidance, and accreditation. Thi…
Multi-modal Representations for Fine-grained Multi-label Critical View of Safety Recognition
Britty Baby, Vinkle Srivastav, Pooja P. Jain +3
The Critical View of Safety (CVS) is crucial for safe laparoscopic cholecystectomy, yet assessing CVS criteria remains a complex and challenging task, even for experts. Traditional…
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…
Surgeons Awareness, Expectations, and Involvement with Artificial Intelligence: a Survey Pre and Post the GPT Era
Lorenzo Arboit, Dennis N. Schneider, Toby Collins +7
Artificial Intelligence (AI) is transforming medicine, with generative AI models like ChatGPT reshaping perceptions of its potential. This study examines surgeons' awareness, expec…
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…
Surgical Text-to-Image Generation
Chinedu Innocent Nwoye, Rupak Bose, Kareem Elgohary +5
Acquiring surgical data for research and development is significantly hindered by high annotation costs and practical and ethical constraints. Utilizing synthetically generated ima…
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…
MOSaiC: a Web-based Platform for Collaborative Medical Video Assessment and Annotation
Jean-Paul Mazellier, Antoine Boujon, Méline Bour-Lang +5
This technical report presents MOSaiC 3.6.2, a web-based collaborative platform designed for the annotation and evaluation of medical videos. MOSaiC is engineered to facilitate vid…
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…