Deep learning methods to generate synthetic CT from MRI in radiotherapy: A literature review

M Boulanger, JC Nunes, H Chourak, A Largent, S Tahri… - Physica Medica, 2021 - Elsevier
Purpose In radiotherapy, MRI is used for target volume and organs-at-risk delineation for its
superior soft-tissue contrast as compared to CT imaging. However, MRI does not provide the …

CT synthesis from MR in the pelvic area using Residual Transformer Conditional GAN

B Zhao, T Cheng, X Zhang, J Wang, H Zhu… - … medical imaging and …, 2023 - Elsevier
Magnetic resonance (MR) image-guided radiation therapy is a hot topic in current radiation
therapy research, which relies on MR to generate synthetic computed tomography (SCT) …

MRI-based treatment planning for proton radiotherapy: dosimetric validation of a deep learning-based liver synthetic CT generation method

Y Liu, Y Lei, Y Wang, T Wang, L Ren… - Physics in Medicine …, 2019 - iopscience.iop.org
Magnetic resonance imaging (MRI) has been widely used in combination with computed
tomography (CT) radiation therapy because MRI improves the accuracy and reliability of …

A deep learning approach to generate synthetic CT in low field MR-guided adaptive radiotherapy for abdominal and pelvic cases

D Cusumano, J Lenkowicz, C Votta, L Boldrini… - Radiotherapy and …, 2020 - Elsevier
Purpose Artificial intelligence (AI) can play a significant role in Magnetic Resonance guided
Radiotherapy (MRgRT), especially to speed up the online adaptive workflow. The aim of this …

Evaluation of a deep learning-based pelvic synthetic CT generation technique for MRI-based prostate proton treatment planning

Y Liu, Y Lei, Y Wang, G Shafai-Erfani… - Physics in Medicine …, 2019 - iopscience.iop.org
The purpose of this work is to validate the application of a deep learning-based method for
pelvic synthetic CT (sCT) generation that can be used for prostate proton beam therapy …

MRI-based treatment planning for liver stereotactic body radiotherapy: validation of a deep learning-based synthetic CT generation method

Y Liu, Y Lei, T Wang, O Kayode, S Tian… - The British Journal of …, 2019 - academic.oup.com
Objective: The purpose of this work is to develop and validate a learning-based method to
derive electron density from routine anatomical MRI for potential MRI-based SBRT treatment …

[HTML][HTML] Magnetic resonance-based synthetic computed tomography images generated using generative adversarial networks for nasopharyngeal carcinoma …

Y Peng, S Chen, A Qin, M Chen, X Gao, Y Liu… - Radiotherapy and …, 2020 - Elsevier
Background and purpose To investigate the feasibility of synthesizing computed tomography
(CT) images from magnetic resonance (MR) images using generative adversarial networks …

Unsupervised pseudo CT generation using heterogenous multicentric CT/MR images and CycleGAN: Dosimetric assessment for 3D conformal radiotherapy

A Jabbarpour, SR Mahdavi, AV Sadr, G Esmaili… - Computers in biology …, 2022 - Elsevier
Purpose Absorbed dose calculation in magnetic resonance-guided radiation therapy
(MRgRT) is commonly based on pseudo CT (pCT) images. This study investigated the …

A deep learning approach to generate synthetic CT in low field MR-guided radiotherapy for lung cases

J Lenkowicz, C Votta, M Nardini, F Quaranta… - Radiotherapy and …, 2022 - Elsevier
Introduction This study aims to apply a conditional Generative Adversarial Network (cGAN)
to generate synthetic Computed Tomography (sCT) from 0.35 Tesla Magnetic Resonance …

Comparison of deep learning-based and patch-based methods for pseudo-CT generation in MRI-based prostate dose planning

A Largent, A Barateau, JC Nunes, E Mylona… - International Journal of …, 2019 - Elsevier
Purpose Deep learning methods (DLMs) have recently been proposed to generate pseudo-
CT (pCT) for magnetic resonance imaging (MRI) based dose planning. This study aims to …