96 citations · 118 across the 5 of their papers we have counts for
3 papers · 1 filter
FDDM: Unsupervised Medical Image Translation with a Frequency-Decoupled Diffusion Model
Yunxiang Li, Hua-Chieh Shao, Xiaoxue Qian +1
Diffusion models have demonstrated significant potential in producing high-quality images in medical image translation to aid disease diagnosis, localization, and treatment. Nevert…
nnSAM: Plug-and-play Segment Anything Model Improves nnUNet Performance
Yunxiang Li, Bowen Jing, Zihan Li +2
Automatic segmentation of medical images is crucial in modern clinical workflows. The Segment Anything Model (SAM) has emerged as a versatile tool for image segmentation without sp…
Zero-shot Medical Image Translation via Frequency-Guided Diffusion Models
Yunxiang Li, Hua-Chieh Shao, Xiao Liang +5
Recently, the diffusion model has emerged as a superior generative model that can produce high quality and realistic images. However, for medical image translation, the existing di…