5 papers
Structure-Adaptive Sparse Diffusion in Voxel Space for 3D Medical Image Enhancement
Hongxu Jiang, Fei Li, Boxiao Yu +4
Three-dimensional (3D) medical image enhancement, including denoising and super-resolution, is critical for clinical diagnosis in CT, PET, and MRI. Although diffusion models have s…
Patlak Parametric Image Estimation from Dynamic PET Using Diffusion Model Prior
Ziqian Huang, Boxiao Yu, Siqi Li +5
Dynamic PET enables the quantitative estimation of physiology-related parameters and is widely utilized in research and increasingly adopted in clinical settings. Parametric imagin…
CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation
Jiong Wu, Yang Xing, Boxiao Yu +2
Most publicly available medical segmentation datasets are only partially labeled, with annotations provided for a subset of anatomical structures. When multiple datasets are combin…
PET Image Denoising via Text-Guided Diffusion: Integrating Anatomical Priors through Text Prompts
Boxiao Yu, Savas Ozdemir, Jiong Wu +4
Low-dose Positron Emission Tomography (PET) imaging presents a significant challenge due to increased noise and reduced image quality, which can compromise its diagnostic accuracy…
Adaptive Whole-Body PET Image Denoising Using 3D Diffusion Models with ControlNet
Boxiao Yu, Kuang Gong
Positron Emission Tomography (PET) is a vital imaging modality widely used in clinical diagnosis and preclinical research but faces limitations in image resolution and signal-to-no…