1 citations · 1 across the 7 of their papers we have counts for
4 papers · 1 filter
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…
Foundation Models for Medical Imaging: Status, Challenges, and Directions
Chuang Niu, Pengwei Wu, Bruno De Man +1
Foundation models (FMs) are rapidly reshaping medical imaging, shifting the field from narrowly trained, task-specific networks toward large, general-purpose models that can be ada…
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…
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…