13 papers
SPIRIT: Spatio-temporal Pairwise Relational Modeling of Instrument-Tissue Interactions for Surgical Action Triplet Recognition
Saurav Sharma, Lorenzo Arboit, Nabani Banik +11
Fine-grained understanding of surgical activity is essential for context-aware assistance in the operating room, including safety monitoring, adverse event identification, and skil…
Where are they looking in the operating room?
Keqi Chen, Séraphin Baributsa, Lilien Schewski +5
Purpose: Gaze-following, the task of inferring where individuals are looking, has been widely studied in computer vision, advancing research in visual attention modeling, social sc…
S4M: 4-points to Segment Anything
Adrien Meyer, Lorenzo Arboit, Giuseppe Massimiani +3
Purpose: The Segment Anything Model (SAM) promises to ease the annotation bottleneck in medical segmentation, but overlapping anatomy and blurred boundaries make its point prompts…
Self-Supervised Uncalibrated Multi-View Video Anonymization in the Operating Room
Keqi Chen, Vinkle Srivastav, Armine Vardazaryan +3
Privacy preservation is a prerequisite for using video data in Operating Room (OR) research. Effective anonymization relies on the exhaustive localization of every individual; even…
DExTeR: Weakly Semi-Supervised Object Detection with Class and Instance Experts for Medical Imaging
Adrien Meyer, Didier Mutter, Nicolas Padoy
Detecting anatomical landmarks in medical imaging is essential for diagnosis and intervention guidance. However, object detection models rely on costly bounding box annotations, li…
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…