1 citations · 1 across the 5 of their papers we have counts for
9 papers
SurgMotion: A Video-Native Foundation Model for Universal Understanding of Surgical Videos
Jinlin Wu, Felix Holm, Chuxi Chen +17
While foundation models have advanced surgical video analysis, current approaches rely predominantly on pixel-level reconstruction objectives that waste model capacity on low-level…
BREATH-VL: Vision-Language-Guided 6-DoF Bronchoscopy Localization via Semantic-Geometric Fusion
Qingyao Tian, Bingyu Yang, Huai Liao +4
Vision-language models (VLMs) have recently shown remarkable performance in navigation and localization tasks by leveraging large-scale pretraining for semantic understanding. Howe…
A Fully Open and Generalizable Foundation Model for Ultrasound Clinical Applications
Hongyuan Zhang, Yuheng Wu, Mingyang Zhao +22
Artificial intelligence (AI) that can effectively learn ultrasound representations by integrating multi-source data holds significant promise for advancing clinical care. However,…
EndoMatcher: Generalizable Endoscopic Image Matcher via Multi-Domain Pre-training for Robot-Assisted Surgery
Bingyu Yang, Qingyao Tian, Yimeng Geng +4
Generalizable dense feature matching in endoscopic images is crucial for robot-assisted tasks, including 3D reconstruction, navigation, and surgical scene understanding. Yet, it re…
Harnessing Foundation Models for Robust and Generalizable 6-DOF Bronchoscopy Localization
Qingyao Tian, Huai Liao, Xinyan Huang +2
Vision-based 6-DOF bronchoscopy localization offers a promising solution for accurate and cost-effective interventional guidance. However, existing methods struggle with 1) limited…
EndoMamba: An Efficient Foundation Model for Endoscopic Videos via Hierarchical Pre-training
Qingyao Tian, Huai Liao, Xinyan Huang +4
Endoscopic video-based tasks, such as visual navigation and surgical phase recognition, play a crucial role in minimally invasive surgeries by providing real-time assistance. While…