78 citations · 124 across the 27 of their papers we have counts for
6 papers · 1 filter
EndoControlMag: Robust Endoscopic Vascular Motion Magnification with Periodic Reference Resetting and Hierarchical Tissue-aware Dual-Mask Control
An Wang, Rulin Zhou, Mengya Xu +7
Visualizing subtle vascular motions in endoscopic surgery is crucial for surgical precision and decision-making, yet remains challenging due to the complex and dynamic nature of su…
SAM Meets Robotic Surgery: An Empirical Study on Generalization, Robustness and Adaptation
An Wang, Mobarakol Islam, Mengya Xu +2
The Segment Anything Model (SAM) serves as a fundamental model for semantic segmentation and demonstrates remarkable generalization capabilities across a wide range of downstream s…
Generalizing Surgical Instruments Segmentation to Unseen Domains with One-to-Many Synthesis
An Wang, Mobarakol Islam, Mengya Xu +1
Despite their impressive performance in various surgical scene understanding tasks, deep learning-based methods are frequently hindered from deploying to real-world surgical applic…
Curriculum-Based Augmented Fourier Domain Adaptation for Robust Medical Image Segmentation
An Wang, Mobarakol Islam, Mengya Xu +1
Accurate and robust medical image segmentation is fundamental and crucial for enhancing the autonomy of computer-aided diagnosis and intervention systems. Medical data collection n…
SME: Spatial-Spectral Mutual Teaching and Ensemble Learning for Scribble-supervised Polyp Segmentation
An Wang, Mengya Xu, Yang Zhang +2
Fully-supervised polyp segmentation has accomplished significant triumphs over the years in advancing the early diagnosis of colorectal cancer. However, label-efficient solutions f…
SAM Meets Robotic Surgery: An Empirical Study in Robustness Perspective
An Wang, Mobarakol Islam, Mengya Xu +2
Segment Anything Model (SAM) is a foundation model for semantic segmentation and shows excellent generalization capability with the prompts. In this empirical study, we investigate…