From the 1 of 5 linked papers with an AI index.
5 papers
FORCE-Interior: Measurement-Consistent Adaptation of a Poisson-Flow Generative Prior for Interior CT
Kang Chen, Wenjun Xia, Jianxu Wang +2
The paper introduces FORCE-Interior, a Poisson‑flow generative reconstruction framework that incorporates measurement‑constrained initialization and per‑step data consistency to im…
Self-Auditing Residual Drifting for Pathology-Preserving Accelerated Knee MRI
Qing Lyu, Jianxu Wang, Mohammad Kawas +2
Accelerated magnetic resonance imaging reduces acquisition time, but reconstruction from undersampled k-space can blur diagnostically relevant structures or introduce failures that…
RDDM: A Residual-Driven Drifting Model for High-Fidelity Low-Dose CT Denoising
Jianxu Wang, Qing Lyu, Ge Wang
Low-dose CT (LDCT) denoising remains an important yet challenging problem in medical imaging. Although recent learning-based methods have shown promising performance, those optimiz…
MRI-to-CT synthesis using drifting models
Qing Lyu, Jianxu Wang, Jeremy Hudson +2
Accurate MRI-to-CT synthesis could enable MR-only pelvic workflows by providing CT-like images with bone details while avoiding additional ionizing radiation. In this work, we inve…
Median2Median: Zero-shot Suppression of Structured Noise in Images
Jianxu Wang, Ge Wang
Image denoising is a fundamental problem in computer vision and medical imaging. However, real-world images are often degraded by structured noise with strong anisotropic correlati…