9 citations · 16 across the 29 of their papers we have counts for
11 papers · 2 filters
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…
End-to-End Learning of Multi-Organ Implicit Surfaces from 3D Medical Imaging Data
Farahdiba Zarin, Nicolas Padoy, Jérémy Dana +1
The fine-grained surface reconstruction of different organs from 3D medical imaging can provide advanced diagnostic support and improved surgical planning. However, the representat…
Recognizing Surgical Phases Anywhere: Few-Shot Test-time Adaptation and Task-graph Guided Refinement
Kun Yuan, Tingxuan Chen, Shi Li +9
The complexity and diversity of surgical workflows, driven by heterogeneous operating room settings, institutional protocols, and anatomical variability, present a significant chal…
Adaptation of Multi-modal Representation Models for Multi-task Surgical Computer Vision
Soham Walimbe, Britty Baby, Vinkle Srivastav +1
Surgical AI often involves multiple tasks within a single procedure, like phase recognition or assessing the Critical View of Safety in laparoscopic cholecystectomy. Traditional mo…
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…