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PoCGM: Poisson-Conditioned Generative Model for Sparse-View CT Reconstruction
Changsheng Fang, Yongtong Liu, Bahareh Morovati +3
In computed tomography (CT), reducing the number of projection views is an effective strategy to lower radiation exposure and/or improve temporal resolution. However, this often re…
ResPF: Residual Poisson Flow for Efficient and Physically Consistent Sparse-View CT Reconstruction
Changsheng Fang, Yongtong Liu, Bahareh Morovati +5
Sparse-view computed tomography (CT) is a practical solution to reduce radiation dose, but the resulting ill-posed inverse problem poses significant challenges for accurate image r…
-NeRF: Leveraging Attenuation Priors in Neural Radiance Field for 3D Computed Tomography Reconstruction
Li Zhou, Changsheng Fang, Bahareh Morovati +4
This paper introduces -NeRF, a self-supervised approach that sets a new standard in novel view synthesis (NVS) and computed tomography (CT) reconstruction by modeling a continuo…
Physics-informed Score-based Diffusion Model for Limited-angle Reconstruction of Cardiac Computed Tomography
Shuo Han, Yongshun Xu, Dayang Wang +5
Cardiac computed tomography (CT) has emerged as a major imaging modality for the diagnosis and monitoring of cardiovascular diseases. High temporal resolution is essential to ensur…
LoMAE: Low-level Vision Masked Autoencoders for Low-dose CT Denoising
Dayang Wang, Yongshun Xu, Shuo Han +4
Low-dose computed tomography (LDCT) offers reduced X-ray radiation exposure but at the cost of compromised image quality, characterized by increased noise and artifacts. Recently,…