59 citations · 92 across the 11 of their papers we have counts for
4 papers · 1 filter
LangMamba: A Language-driven Mamba Framework for Low-dose CT Denoising with Vision-language Models
Zhihao Chen, Tao Chen, Chenhui Wang +5
Low-dose computed tomography (LDCT) reduces radiation exposure but often degrades image quality, potentially compromising diagnostic accuracy. Existing deep learning-based denoisin…
Noise-Inspired Diffusion Model for Generalizable Low-Dose CT Reconstruction
Qi Gao, Zhihao Chen, Dong Zeng +3
The generalization of deep learning-based low-dose computed tomography (CT) reconstruction models to doses unseen in the training data is important and remains challenging. Previou…
Patient-Level Anatomy Meets Scanning-Level Physics: Personalized Federated Low-Dose CT Denoising Empowered by Large Language Model
Ziyuan Yang, Yingyu Chen, Zhiwen Wang +3
Reducing radiation doses benefits patients, however, the resultant low-dose computed tomography (LDCT) images often suffer from clinically unacceptable noise and artifacts. While d…
Autoregressive Medical Image Segmentation via Next-Scale Mask Prediction
Tao Chen, Chenhui Wang, Zhihao Chen +1
While deep learning has significantly advanced medical image segmentation, most existing methods still struggle with handling complex anatomical regions. Cascaded or deep supervisi…