A review on deep learning in medical image reconstruction

HM Zhang, B Dong - Journal of the Operations Research Society of China, 2020 - Springer
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 …

A review on deep learning approaches for low-dose computed tomography restoration

KASH Kulathilake, NA Abdullah, AQM Sabri… - Complex & Intelligent …, 2023 - Springer
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 …

Low-dose CT with a residual encoder-decoder convolutional neural network

H Chen, Y Zhang, MK Kalra, F Lin… - IEEE transactions on …, 2017 - ieeexplore.ieee.org
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 …

Multi-channel optimization generative model for stable ultra-sparse-view CT reconstruction

W Wu, J Pan, Y Wang, S Wang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
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 …

A sparse-view CT reconstruction method based on combination of DenseNet and deconvolution

Z Zhang, X Liang, X Dong, Y **e… - IEEE transactions on …, 2018 - ieeexplore.ieee.org
Sparse-view computed tomography (CT) holds great promise for speeding up data
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

H Shan, Y Zhang, Q Yang, U Kruger… - IEEE transactions on …, 2018 - ieeexplore.ieee.org
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 …

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 …

LEARN: Learned experts' assessment-based reconstruction network for sparse-data CT

H Chen, Y Zhang, Y Chen, J Zhang… - IEEE transactions on …, 2018 - ieeexplore.ieee.org
Compressive sensing (CS) has proved effective for tomographic reconstruction from
sparsely collected data or under-sampled measurements, which are practically important for …

Domain progressive 3D residual convolution network to improve low-dose CT imaging

X Yin, Q Zhao, J Liu, W Yang, J Yang… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
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 …

TransCT: dual-path transformer for low dose computed tomography

Z Zhang, L Yu, X Liang, W Zhao, L **ng - … 1, 2021, Proceedings, Part VI 24, 2021 - Springer
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 …