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A review on deep learning in medical image reconstruction
Medical imaging is crucial in modern clinics to provide guidance to the diagnosis and
treatment of diseases. Medical image reconstruction is one of the most fundamental and …
treatment of diseases. Medical image reconstruction is one of the most fundamental and …
A review on deep learning approaches for low-dose computed tomography restoration
Computed Tomography (CT) is a widely use medical image modality in clinical medicine,
because it produces excellent visualizations of fine structural details of the human body. In …
because it produces excellent visualizations of fine structural details of the human body. In …
Low-dose CT with a residual encoder-decoder convolutional neural network
Given the potential risk of X-ray radiation to the patient, low-dose CT has attracted a
considerable interest in the medical imaging field. Currently, the main stream low-dose CT …
considerable interest in the medical imaging field. Currently, the main stream low-dose CT …
Multi-channel optimization generative model for stable ultra-sparse-view CT reconstruction
Score-based generative model (SGM) has risen to prominence in sparse-view CT
reconstruction due to its impressive generation capability. The consistency of data is crucial …
reconstruction due to its impressive generation capability. The consistency of data is crucial …
A sparse-view CT reconstruction method based on combination of DenseNet and deconvolution
Sparse-view computed tomography (CT) holds great promise for speeding up data
acquisition and reducing radiation dose in CT scans. Recent advances in reconstruction …
acquisition and reducing radiation dose in CT scans. Recent advances in reconstruction …
3-D convolutional encoder-decoder network for low-dose CT via transfer learning from a 2-D trained network
Low-dose computed tomography (LDCT) has attracted major attention in the medical
imaging field, since CT-associated X-ray radiation carries health risks for patients. The …
imaging field, since CT-associated X-ray radiation carries health risks for patients. The …
Low-dose CT via convolutional neural network
H Chen, Y Zhang, W Zhang, P Liao, K Li… - Biomedical optics …, 2017 - opg.optica.org
In order to reduce the potential radiation risk, low-dose CT has attracted an increasing
attention. However, simply lowering the radiation dose will significantly degrade the image …
attention. However, simply lowering the radiation dose will significantly degrade the image …
LEARN: Learned experts' assessment-based reconstruction network for sparse-data CT
Compressive sensing (CS) has proved effective for tomographic reconstruction from
sparsely collected data or under-sampled measurements, which are practically important for …
sparsely collected data or under-sampled measurements, which are practically important for …
Domain progressive 3D residual convolution network to improve low-dose CT imaging
The wide applications of X-ray computed tomography (CT) bring low-dose CT (LDCT) into a
clinical prerequisite, but reducing the radiation exposure in CT often leads to significantly …
clinical prerequisite, but reducing the radiation exposure in CT often leads to significantly …
TransCT: dual-path transformer for low dose computed tomography
Low dose computed tomography (LDCT) has attracted more and more attention in routine
clinical diagnosis assessment, therapy planning, etc., which can reduce the dose of X-ray …
clinical diagnosis assessment, therapy planning, etc., which can reduce the dose of X-ray …