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: Propagating Sparse Video Annotations via Implicit Neural Feature Matching
Zhuorui Zhang, Roger Pallarès-López, Praneeth Namburi +1
Acquiring per-frame video annotations remains a primary bottleneck for deploying computer vision in specialized domains such as medical imaging, where expert labeling is slow and c…
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…