9 citations · 18 across the 8 of their papers we have counts for
8 papers
Improving Cross-Site Whole-Heart Segmentation
Tanish Mudaliar, Justin Li, Daniel Lin +4
Whole-heart segmentation from CT and MRI is essential for quantitative cardiac image analysis, but remains challenging under multi-center and multi-modality distribution shift. In…
Evidence-Based Actor-Verifier Reasoning for Echocardiographic Agents
Peng Huang, Yiming Wang, Yineng Chen +9
Echocardiography plays an important role in the screening and diagnosis of cardiovascular diseases. However, automated intelligent analysis of echocardiographic data remains challe…
Diffusion-empowered AutoPrompt MedSAM
Peng Huang, Shu Hu, Bo Peng +5
MedSAM, a medical foundation model derived from the SAM architecture, has demonstrated notable success across diverse medical domains. However, its clinical application faces two m…
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…