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03/22/2023
Cube-Based 3D Denoising Diffusion Probabilistic Model for Cone Beam Computed Tomography Reconstruction with Incomplete Data
Deep learning (DL) has been extensively researched in the field of compu...
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11/18/2022
Patch-Based Denoising Diffusion Probabilistic Model for Sparse-View CT Reconstruction
Sparse-view computed tomography (CT) can be used to reduce radiation dos...
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06/08/2022
Hypernetwork-based Personalized Federated Learning for Multi-Institutional CT Imaging
Computed tomography (CT) is of great importance in clinical practice due...
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03/29/2022
Synergizing Physics/Model-based and Data-driven Methods for Low-Dose CT
Since 2016, deep learning (DL) has advanced tomographic imaging with rem...
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10/29/2021
Unsupervised PET Reconstruction from a Bayesian Perspective
Positron emission tomography (PET) reconstruction has become an ill-pose...
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05/14/2021
One Network to Solve Them All: A Sequential Multi-Task Joint Learning Network Framework for MR Imaging Pipeline
Magnetic resonance imaging (MRI) acquisition, reconstruction, and segmen...
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04/27/2021
Provably Convergent Learned Inexact Descent Algorithm for Low-Dose CT Reconstruction
We propose a provably convergent method, called Efficient Learned Descen...
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04/03/2021
IDOL-Net: An Interactive Dual-Domain Parallel Network for CT Metal Artifact Reduction
Due to the presence of metallic implants, the imaging quality of compute...
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03/24/2021
MANAS: Multi-Scale and Multi-Level Neural Architecture Search for Low-Dose CT Denoising
Lowering the radiation dose in computed tomography (CT) can greatly redu...
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02/16/2021
DAN-Net: Dual-Domain Adaptive-Scaling Non-local Network for CT Metal Artifact Reduction
Metal implants can heavily attenuate X-rays in computed tomography (CT) ...
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12/13/2020
LEARN++: Recurrent Dual-Domain Reconstruction Network for Compressed Sensing CT
Compressed sensing (CS) computed tomography has been proven to be import...
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10/27/2020
Fourth-Order Nonlocal Tensor Decomposition Model for Spectral Computed Tomography
Spectral computed tomography (CT) can reconstruct spectral images from d...
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10/27/2020
CT Reconstruction with PDF: Parameter-Dependent Framework for Multiple Scanning Geometries and Dose Levels
Current mainstream of CT reconstruction methods based on deep learning u...
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03/20/2019
Convolutional Sparse Coding for Compressed Sensing CT Reconstruction
Over the past few years, dictionary learning (DL)-based methods have bee...
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10/15/2018
