From the 1 of 7 linked papers with an AI index.
7 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…
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…
Development and Validation of a Large Language Model for Generating Fully-Structured Radiology Reports
Chuang Niu, Md Sayed Tanveer, Md Zabirul Islam +5
Current LLMs for creating fully-structured reports face the challenges of formatting errors, content hallucinations, and privacy leakage issues when uploading data to external serv…
Reasoning Language Model for Personalized Lung Cancer Screening
Chuang Niu, Ge Wang
Accurate risk assessment in lung cancer screening is critical for enabling early cancer detection and minimizing unnecessary invasive procedures. The Lung CT Screening Reporting an…
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…