Background Sparse-view computed tomography (CT) reduces radiation exposure but suffers from severe artifacts caused by insufficient sampling and data scarcity, which compromise image fidelity. Recen...
We present a flexible framework for robust computed tomography (CT) reconstruction with a specific emphasis on recovering thin ID and 2D manifolds embedded in 3D volumes. To reconstruct such structures at resolutions below the Nyquist limit of the CT image sensor, we devise a new 3D structure ...
We present a flexible framework for robust computed tomog-raphy (CT) reconstruction with a specific emphasis on recovering thin 1D and 2D manifolds embedded in 3D volumes. To reconstruct such structures at resolutions below the Nyquist limit of the CT image sensor, we devise a new 3D structure...
C ONDITIONING G ENERATIVE L ATENT O PTIMIZATION FORS PARSE -V IEW CT I MAGE R ECONSTRUCTIONThomas Braure 1 , Delphine Lazaro 2 , David Hateau 1 , Vincent Brandon 1 , and Kévin Ginsburger 11 CEA DIF, 91297 Arpajon Cedex, France2 CEA LIST, 91191 Gif-sur-Yvette Cedex, FranceMay 1...
IntroductionLow-dose computed tomography (CT) image reconstruc-tion has been widely used in industrial CT and medical CT [1]. In the medical CT fi eld, sparse-view sampling has prac-tical implications in reducing ionizing radiation, which is harmful to people’s health, decreasing the scanning...
The proposed unsupervised deep learning in sinogram domain for sparse-view CT. Top: Training stage to learn the gradient distribution via denoising score matching. Bottom: Iterate between numerical SDE solver and data-consistency step to achieve reconstruction. DC stands for the data-consistency items...
PDF Tools Share Abstract Background: Sparse-view CT image reconstruction problems encountered in dynamic CT acquisitions are technically challenging. Recently, many deep learning strategies have been proposed to reconstruct CT images from sparse-view angle acquisitions showing promising results. However, two...
Sparse-view image reconstruction in inverse-geometry CT (IGCT) for fast, low-dose, volumetric dental X-ray imagingComputed tomographyInverse-geometry CTDental X-ray imagingTotal variationAs a new direction for computed tomography (CT) imaging, inverse-geometry CT (IGCT) has been recently introduced...
Stage-by-stage Wavelet Optimization Refinement Diffusion Model for Sparse-view CT Reconstruction - yqx7150/SWORD
Sparse-view Reconstruction can be used to provide accelerated low dose CT imaging with both accelerated scan and reduced projection/back-projection calculation. Despite the rapid developments, image noise and artifacts still remain a major issue in the low dose protocol. In this paper, a deep learn...