42 citations · 103 across the 10 of their papers we have counts for
3 papers · 1 filter
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…