4 papers
Cohort-Scale Neural Atlases of Ultrasound Video
Zhuorui Zhang, Roger Pallarès-López, Xuan Wu +2
Ultrasound is the most widely used real-time imaging modality in clinical practice, yet per-frame video annotation remains a major bottleneck: expert labels are scarce and costly,…
Match4Annotate: Cross-Video Annotation Transfer in Ultrasound via Implicit Feature Flow-Guided Matching
Zhuorui Zhang, Roger Pallarès-López, Praneeth Namburi +1
Acquiring per-frame annotations for ultrasound videos is costly and requires clinical expertise, limiting learning-based analysis. We study cross-video annotation transfer: propaga…
Surg-R1: A Hierarchical Reasoning Foundation Model for Scalable and Interpretable Surgical Decision Support with Multi-Center Clinical Validation
Jian Jiang, Chenxi Lin, Yiming Gu +24
Surgical scene understanding demands not only accurate predictions but also interpretable reasoning that surgeons can verify against clinical expertise. However, existing surgical…
Increasing LLM response trustworthiness using voting ensembles
Aparna Nair-Kanneganti, Trevor J. Chan, Shir Goldfinger +3
Despite huge advances, LLMs still lack convenient and reliable methods to quantify the uncertainty in their responses, making them difficult to trust in high-stakes applications. O…