CBCT‐based synthetic CT generation using deep‐attention cycleGAN for pancreatic adaptive radiotherapy
Purpose Current clinical application of cone‐beam CT (CBCT) is limited to patient setup.
Imaging artifacts and Hounsfield unit (HU) inaccuracy make the process of CBCT‐based …
Imaging artifacts and Hounsfield unit (HU) inaccuracy make the process of CBCT‐based …
Generation of abdominal synthetic CTs from 0.35 T MR images using generative adversarial networks for MR-only liver radiotherapy
Electron density maps must be accurately estimated to achieve valid dose calculation in MR-
only radiotherapy. The goal of this study is to assess whether two deep learning models, the …
only radiotherapy. The goal of this study is to assess whether two deep learning models, the …
Generating synthesized computed tomography (CT) from cone-beam computed tomography (CBCT) using CycleGAN for adaptive radiation therapy
Throughout the course of delivering a radiation therapy treatment, which may take several
weeks, a patient's anatomy may change drastically, and adaptive radiation therapy (ART) …
weeks, a patient's anatomy may change drastically, and adaptive radiation therapy (ART) …
Evaluation of a cycle-generative adversarial network-based cone-beam CT to synthetic CT conversion algorithm for adaptive radiation therapy
M Eckl, L Hoppen, GR Sarria, J Boda-Heggemann… - Physica Medica, 2020 - Elsevier
Purpose Image-guided radiation therapy could benefit from implementing adaptive radiation
therapy (ART) techniques. A cycle-generative adversarial network (cycle-GAN)-based cone …
therapy (ART) techniques. A cycle-generative adversarial network (cycle-GAN)-based cone …
[HTML][HTML] Generating synthetic CT from low-dose cone-beam CT by using generative adversarial networks for adaptive radiotherapy
L Gao, K Xie, X Wu, Z Lu, C Li, J Sun, T Lin, J Sui… - Radiation Oncology, 2021 - Springer
Objective To develop high-quality synthetic CT (sCT) generation method from low-dose
cone-beam CT (CBCT) images by using attention-guided generative adversarial networks …
cone-beam CT (CBCT) images by using attention-guided generative adversarial networks …
[HTML][HTML] Imaging study of pseudo-CT synthesized from cone-beam CT based on 3D CycleGAN in radiotherapy
H Sun, R Fan, C Li, Z Lu, K Xie, X Ni, J Yang - Frontiers in oncology, 2021 - frontiersin.org
Purpose To propose a synthesis method of pseudo-CT (CTCycleGAN) images based on an
improved 3D cycle generative adversarial network (CycleGAN) to solve the limitations of …
improved 3D cycle generative adversarial network (CycleGAN) to solve the limitations of …
MRI-based treatment planning for proton radiotherapy: dosimetric validation of a deep learning-based liver synthetic CT generation method
Magnetic resonance imaging (MRI) has been widely used in combination with computed
tomography (CT) radiation therapy because MRI improves the accuracy and reliability of …
tomography (CT) radiation therapy because MRI improves the accuracy and reliability of …
Learning‐based CBCT correction using alternating random forest based on auto‐context model
Purpose Quantitative Cone Beam CT (CBCT) imaging is increasing in demand for precise
image‐guided radiotherapy because it provides a foundation for advanced image‐guided …
image‐guided radiotherapy because it provides a foundation for advanced image‐guided …
Synthetic CT generation from CBCT images via unsupervised deep learning
Abstract Adaptive-radiation-therapy (ART) is applied to account for anatomical variations
observed over the treatment course. Daily or weekly cone-beam computed tomography …
observed over the treatment course. Daily or weekly cone-beam computed tomography …
CBCT‐Based synthetic CT image generation using conditional denoising diffusion probabilistic model
Background Daily or weekly cone‐beam computed tomography (CBCT) scans are
commonly used for accurate patient positioning during the image‐guided radiotherapy …
commonly used for accurate patient positioning during the image‐guided radiotherapy …