3 papers
cs.CV2025
Hybrid Transformer-Mamba for Weakly Supervised Volumetric Medical Segmentation
Yiheng Lyu, Lian Xu, Coen Arrow +3
Weakly supervised segmentation enables model training from plane-level labels. Existing methods often rely on 2D encoders, neglecting the volumetric nature of medical data. We prop…
cs.CV2025
MoSFormer: Augmenting Temporal Context with Memory of Surgery for Surgical Phase Recognition
Hao Ding, Xu Lian, Mathias Unberath
Surgical phase recognition from video enables various downstream applications. Transformer-based sliding window approaches have set the state-of-the-art by capturing rich spatial-t…
cs.CV2024
Towards Robust Algorithms for Surgical Phase Recognition via Digital Twin Representation
Hao Ding, Yuqian Zhang, Wenzheng Cheng +7
Surgical phase recognition (SPR) is an integral component of surgical data science, enabling high-level surgical analysis. End-to-end trained neural networks that predict surgical…