9 citations · 18 across the 8 of their papers we have counts for
5 papers · 1 filter
An Uncertainty-Aware Generalization Framework for Cardiovascular Image Segmentation
Ting Yu Tsai, Liangqiao Gui, Yineng Chen +8
Deep learning models have achieved significant success in segmenting cardiovascular structures, but there is a growing need to improve their generalization and robustness. Current…
Challenge Summary U-MedSAM: Uncertainty-aware MedSAM for Medical Image Segmentation
Xin Wang, Xiaoyu Liu, Peng Huang +3
Medical Image Foundation Models have proven to be powerful tools for mask prediction across various datasets. However, accurately assessing the uncertainty of their predictions rem…
UU-Mamba: Uncertainty-aware U-Mamba for Cardiac Image Segmentation
Ting Yu Tsai, Li Lin, Shu Hu +3
Biomedical image segmentation is critical for accurate identification and analysis of anatomical structures in medical imaging, particularly in cardiac MRI. Manual segmentation is…
Neural Radiance Fields in Medical Imaging: A Survey
Xin Wang, Yineng Chen, Shu Hu +3
Neural Radiance Fields (NeRF), as a pioneering technique in computer vision, offer great potential to revolutionize medical imaging by synthesizing three-dimensional representation…
Artificial Intelligence in Image-based Cardiovascular Disease Analysis
Xin Wang, Mingcheng Hu, Connie W. Tsao +1
Recent advancements in Artificial Intelligence (AI) have significantly influenced the field of Cardiovascular Disease (CVD) analysis, particularly in image-based diagnostics. Our p…