6 papers · 1 filter
SONAR: A Structure-Consistent Neural Operator for Null-Space-Aware Sparse View CT Reconstruction
Song Ni, Haijun Yu, Haodong Li +4
Sparse-view computed tomography (CT) reduces radiation dose and acquisition time but remains severely ill-posed because incomplete projections poorly constrain null-space informati…
Medical Foundation Model Features as Perceptual Loss for Brain MRI Contrast Dose Simulation
Changsheng Fang, Dayang Wang, T. Campbell Arnold +2
Perceptual losses are widely used in medical image synthesis because they encourage agreement in high-level structure beyond voxel-wise intensity similarity. In practice, most perc…
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…
Cross-Distribution Diffusion Priors-Driven Iterative Reconstruction for Sparse-View CT
Haodong Li, Shuo Han, Haiyang Mao +5
Sparse-View CT (SVCT) reconstruction enhances temporal resolution and reduces radiation dose, yet its clinical use is hindered by artifacts due to view reduction and domain shifts…
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…