Compensation cycle consistent generative adversarial networks (Comp‐GAN) for synthetic CT generation from MR scans with truncated anatomy

Y Zhao, H Wang, C Yu, LE Court, X Wang… - Medical …, 2023 - Wiley Online Library
Background MR scans used in radiotherapy can be partially truncated due to the limited field
of view (FOV), affecting dose calculation accuracy in MR‐based radiation treatment …

SC-GAN: Structure-completion generative adversarial network for synthetic CT generation from MR images with truncated anatomy

X Chen, Y Zhao, LE Court, H Wang, T Pan… - … Medical Imaging and …, 2024 - Elsevier
Creating synthetic CT (sCT) from magnetic resonance (MR) images enables MR-based
treatment planning in radiation therapy. However, the MR images used for MR-guided …

MRI‐only based synthetic CT generation using dense cycle consistent generative adversarial networks

Y Lei, J Harms, T Wang, Y Liu, HK Shu, AB Jani… - Medical …, 2019 - Wiley Online Library
Purpose Automated synthetic computed tomography (sCT) generation based on magnetic
resonance imaging (MRI) images would allow for MRI‐only based treatment planning in …

[HTML][HTML] CBCT-based synthetic CT generation using generative adversarial networks with disentangled representation

J Liu, H Yan, H Cheng, J Liu, P Sun… - … Imaging in Medicine …, 2021 - ncbi.nlm.nih.gov
Background Cone-beam computed tomography (CBCT) plays a key role in image-guided
radiotherapy (IGRT), however its poor image quality limited its clinical application. In this …

Attention-guided generative adversarial network to address atypical anatomy in synthetic CT generation

H Emami, M Dong… - 2020 IEEE 21st …, 2020 - ieeexplore.ieee.org
Recently, interest in MR-only treatment planning using synthetic CTs (synCTs) has grown
rapidly in radiation therapy. However, developing class solutions for medical images that …

Improving generalization in MR‐to‐CT synthesis in radiotherapy by using an augmented cycle generative adversarial network with unpaired data

KND Brou Boni, J Klein, A Gulyban, N Reynaert… - Medical …, 2021 - Wiley Online Library
Purpose MR‐to‐CT synthesis is one of the first steps in the establishment of an MRI‐only
workflow in radiotherapy. Current MR‐to‐CT synthesis methods in deep learning use …

Multi‐sequence MR image‐based synthetic CT generation using a generative adversarial network for head and neck MRI‐only radiotherapy

M Qi, Y Li, A Wu, Q Jia, B Li, W Sun, Z Dai, X Lu… - Medical …, 2020 - Wiley Online Library
Purpose The purpose of this study is to investigate the effect of different magnetic resonance
(MR) sequences on the accuracy of deep learning‐based synthetic computed tomography …

Generating synthetic CTs from magnetic resonance images using generative adversarial networks

H Emami, M Dong, SP Nejad‐Davarani… - Medical …, 2018 - Wiley Online Library
Purpose While MR‐only treatment planning using synthetic CTs (synCTs) offers potential for
streamlining clinical workflow, a need exists for an efficient and automated synCT …

Channel-wise attention enhanced and structural similarity constrained cycleGAN for effective synthetic CT generation from head and neck MRI images

C Gong, Y Huang, M Luo, S Cao, X Gong, S Ding… - Radiation …, 2024 - Springer
Background Magnetic resonance imaging (MRI) plays an increasingly important role in
radiotherapy, enhancing the accuracy of target and organs at risk delineation, but the …

Structurally-constrained optical-flow-guided adversarial generation of synthetic CT for MR-only radiotherapy treatment planning

R Vajpayee, V Agrawal, G Krishnamurthi - Scientific Reports, 2022 - nature.com
The rapid progress in image-to-image translation methods using deep neural networks has
led to advancements in the generation of synthetic CT (sCT) in MR-only radiotherapy …