6 papers
Weight Group-wise Post-Training Quantization for Medical Foundation Model
Yineng Chen, Peng Huang, Aozhong Zhang +9
Foundation models have achieved remarkable results in medical image analysis. However, its large network architecture and high computational complexity significantly impact inferen…
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 Explainable Non-local Network for COVID-19 Diagnosis
Jingfu Yang, Peng Huang, Jing Hu +5
The CNN has achieved excellent results in the automatic classification of medical images. In this study, we propose a novel deep residual 3D attention non-local network (NL-RAN) to…
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…
Robustly Optimized Deep Feature Decoupling Network for Fatty Liver Diseases Detection
Peng Huang, Shu Hu, Bo Peng +3
Current medical image classification efforts mainly aim for higher average performance, often neglecting the balance between different classes. This can lead to significant differe…