4 papers
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…
Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation
Juntong Fan, Shuyi Fan, Debesh Jha +4
Accurate endoscopic image segmentation on the polyps is critical for early colorectal cancer detection. However, this task remains challenging due to low contrast with surrounding…
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…