4 citations · 7 across the 7 of their papers we have counts for
7 papers
FORCE-Interior: Measurement-Consistent Adaptation of a Poisson-Flow Generative Prior for Interior CT
Kang Chen, Wenjun Xia, Jianxu Wang +2
Interior tomography reconstructs a region of interest (ROI) from truncated projections, an ill-posed problem with non-unique solutions and truncation-induced bias. Existing deep-le…
Poisson Flow Consistency Training
Anthony Zhang, Mahmut Gokmen, Dennis Hein +4
The Poisson Flow Consistency Model (PFCM) is a consistency-style model based on the robust Poisson Flow Generative Model++ (PFGM++) which has achieved success in unconditional imag…
Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine
Wenjun Xia, Chuang Niu, Ge Wang
Computed tomography (CT) is a major medical imaging modality. Clinical CT scenarios, such as low-dose screening, sparse-view scanning, and metal implants, often lead to severe nois…
Information-Maximized Soft Variable Discretization for Self-Supervised Image Representation Learning
Chuang Niu, Wenjun Xia, Hongming Shan +1
Self-supervised learning (SSL) has emerged as a crucial technique in image processing, encoding, and understanding, especially for developing today's vision foundation models that…
Diffusion Prior Regularized Iterative Reconstruction for Low-dose CT
Wenjun Xia, Yongyi Shi, Chuang Niu +2
Computed tomography (CT) involves a patient's exposure to ionizing radiation. To reduce the radiation dose, we can either lower the X-ray photon count or down-sample projection vie…
Blind CT Image Quality Assessment Using DDPM-derived Content and Transformer-based Evaluator
Yongyi Shi, Wenjun Xia, Ge Wang +1
Lowering radiation dose per view and utilizing sparse views per scan are two common CT scan modes, albeit often leading to distorted images characterized by noise and streak artifa…
Enabling Competitive Performance of Medical Imaging with Diffusion Model-generated Images without Privacy Leakage
Yongyi Shi, Wenjun Xia, Chuang Niu +2
Deep learning methods have impacted almost every research field, demonstrating notable successes in medical imaging tasks such as denoising and super-resolution. However, the prere…