Synthetic CT generation based on multi-sequence MR using CycleGAN for head and neck MRI-only planning

L Deng, S Chen, Y Li, S Huang, X Yang… - Biomedical Engineering …, 2024 - Springer
The purpose of this study is to investigate the influence of different magnetic resonance (MR)
sequences on the accuracy of generating computed tomography (sCT) images for …

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 …

Multi-Sequence Fusion Network via Single-Sequence CycleGANs for Improved Synthetic CT in Nasopharyngeal Carcinoma Treatment Planning

Y Liu, M Chen, J Zhang, Y Wang, H Gu, C Zhao… - IEEE …, 2024 - ieeexplore.ieee.org
To investigate the effect of different MR sequences on the accuracy of Cycle-consistent
Generative Adversarial Network (CycleGAN) based synthetic CT (sCT) generation in …

Multisequence MR‐generated sCT is promising for HNC MR‐only RT: A comprehensive evaluation of previously developed sCT generation networks

M Qi, Y Li, A Wu, X Lu, L Zhou, T Song - Medical Physics, 2022 - Wiley Online Library
Purpose To verify the feasibility of our in‐house developed multisequence magnetic
resonance (MR)‐generated synthetic computed tomography (sCT) for accurate dose …

[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 …

Head-and-Neck MRI-only radiotherapy treatment planning: From acquisition in treatment position to pseudo-CT generation

A Largent, L Marage, I Gicquiau, JC Nunes… - Cancer …, 2020 - Elsevier
Purpose In context of head-and-neck radiotherapy, this study aims to compare MR image
quality according to diagnostic (DIAG) and radiotherapy (RT) setups; and to optimise an MRI …

Pseudo‐CT generation from multi‐parametric MRI using a novel multi‐channel multi‐path conditional generative adversarial network for nasopharyngeal carcinoma …

X Tie, SK Lam, Y Zhang, KH Lee, KH Au… - Medical physics, 2020 - Wiley Online Library
Purpose To develop and evaluate a novel method for pseudo‐CT generation from multi‐
parametric MR images using multi‐channel multi‐path generative adversarial network …

Dosimetric evaluation of synthetic CT for head and neck radiotherapy generated by a patch‐based three‐dimensional convolutional neural network

AM Dinkla, MC Florkow, M Maspero… - Medical …, 2019 - Wiley Online Library
Purpose To develop and evaluate a patch‐based convolutional neural network (CNN) to
generate synthetic computed tomography (sCT) images for magnetic resonance (MR)‐only …

CBCT-based synthetic CT generated using CycleGAN with HU correction for adaptive radiotherapy of nasopharyngeal carcinoma

C Jihong, Q Kerun, C Kaiqiang, Z Xiuchun, Z Yimin… - Scientific Reports, 2023 - nature.com
This study aims to utilize a hybrid approach of phantom correction and deep learning for
synthesized CT (sCT) images generation based on cone-beam CT (CBCT) images for …

Deep learning MRI-only synthetic-CT generation for pelvis, brain and head and neck cancers

D Bird, R Speight, S Andersson, J Wingqvist… - Radiotherapy and …, 2024 - Elsevier
Background and purpose MRI-only planning relies on dosimetrically accurate synthetic-CT
(sCT) generation to allow dose calculation. Here we validated the dosimetric accuracy of …