A review of deep learning ct reconstruction from incomplete projection data
Computed tomography (CT) is a widely used imaging technique in both medical and
industrial applications. However, accurate CT reconstruction requires complete projection …
industrial applications. However, accurate CT reconstruction requires complete projection …
[HTML][HTML] SYNAPSE: An international roadmap to large brain imaging
APJ Stampfl, Z Liu, J Hu, K Sawada, H Takano… - Physics Reports, 2023 - Elsevier
Since 2020, synchrotron radiation facilities in several Asia-Pacific countries have been
collaborating in a major project called “SYNAPSE”(Synchrotrons for Neuroscience: an Asia …
collaborating in a major project called “SYNAPSE”(Synchrotrons for Neuroscience: an Asia …
DOLCE: A model-based probabilistic diffusion framework for limited-angle ct reconstruction
Abstract Limited-Angle Computed Tomography (LACT) is a non-destructive 3D imaging
technique used in a variety of applications ranging from security to medicine. The limited …
technique used in a variety of applications ranging from security to medicine. The limited …
Iterative residual optimization network for limited-angle tomographic reconstruction
Limited-angle tomographic reconstruction is one of the typical ill-posed inverse problems,
leading to edge divergence with degraded image quality. Recently, deep learning has been …
leading to edge divergence with degraded image quality. Recently, deep learning has been …
Time-reversion fast-sampling score-based model for limited-angle CT reconstruction
Y Wang, Z Li, W Wu - IEEE Transactions on Medical Imaging, 2024 - ieeexplore.ieee.org
The score-based generative model (SGM) has received significant attention in the field of
medical imaging, particularly in the context of limited-angle computed tomography (LACT) …
medical imaging, particularly in the context of limited-angle computed tomography (LACT) …
TIME-Net: Transformer-integrated multi-encoder network for limited-angle artifact removal in dual-energy CBCT
Dual-energy cone-beam computed tomography (DE-CBCT) is a promising imaging
technique with foreseeable clinical applications. DE-CBCT images acquired with two …
technique with foreseeable clinical applications. DE-CBCT images acquired with two …
Sam's net: a self-augmented multistage deep-learning network for end-to-end reconstruction of limited angle CT
Limited angle reconstruction is a typical ill-posed problem in computed tomography (CT).
Given incomplete projection data, images reconstructed by conventional analytical …
Given incomplete projection data, images reconstructed by conventional analytical …
Sparse-view and limited-angle CT reconstruction with untrained networks and deep image prior
Z Shu, A Entezari - Computer Methods and Programs in Biomedicine, 2022 - Elsevier
Background and objective: Neural network based image reconstruction methods are
becoming increasingly popular. However, limited training data and the lack of theoretical …
becoming increasingly popular. However, limited training data and the lack of theoretical …
PIE-ARNet: Prior image enhanced artifact removal network for limited-angle DECT
Dual-energy computed tomography (DECT) is of great clinical significance because it can
simultaneously visualize the internal structure of the scanned object and provide material …
simultaneously visualize the internal structure of the scanned object and provide material …
DPI-MoCo: Deep Prior Image Constrained Motion Compensation Reconstruction for 4D CBCT
4D cone-beam computed tomography (CBCT) plays a critical role in adaptive radiation
therapy for lung cancer. However, extremely sparse sampling projection data will cause …
therapy for lung cancer. However, extremely sparse sampling projection data will cause …