Artificial intelligence in radiotherapy
G Li, X Wu, X Ma - Seminars in Cancer Biology, 2022 - Elsevier
Radiotherapy is a discipline closely integrated with computer science. Artificial intelligence
(AI) has developed rapidly over the past few years. With the explosive growth of medical big …
(AI) has developed rapidly over the past few years. With the explosive growth of medical big …
MRI-LINAC: A transformative technology in radiation oncology
Advances in radiotherapy technologies have enabled more precise target guidance,
improved treatment verification, and greater control and versatility in radiation delivery …
improved treatment verification, and greater control and versatility in radiation delivery …
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) …
therapy research, which relies on MR to generate synthetic computed tomography (SCT) …
Synthetic CT generation from MRI using 3D transformer‐based denoising diffusion model
Background and purpose Magnetic resonance imaging (MRI)‐based synthetic computed
tomography (sCT) simplifies radiation therapy treatment planning by eliminating the need for …
tomography (sCT) simplifies radiation therapy treatment planning by eliminating the need for …
A systematic collection of medical image datasets for deep learning
The astounding success made by artificial intelligence in healthcare and other fields proves
that it can achieve human-like performance. However, success always comes with …
that it can achieve human-like performance. However, success always comes with …
Compensation cycle consistent generative adversarial networks (Comp‐GAN) for synthetic CT generation from MR scans with truncated anatomy
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 …
of view (FOV), affecting dose calculation accuracy in MR‐based radiation treatment …
Review and recommendations on deformable image registration uncertainties for radiotherapy applications
Deformable image registration (DIR) is a versatile tool used in many applications in
radiotherapy (RT). DIR algorithms have been implemented in many commercial treatment …
radiotherapy (RT). DIR algorithms have been implemented in many commercial treatment …
A high-performance method of deep learning for prostate MR-only radiotherapy planning using an optimized Pix2Pix architecture
S Tahri, A Barateau, C Cadin, H Chourak, S Ribault… - Physica Medica, 2022 - Elsevier
Purpose The first aim was to generate and compare synthetic-CT (sCT) images using a
conditional generative adversarial network (cGAN) method (Pix2Pix) for MRI-only prostate …
conditional generative adversarial network (cGAN) method (Pix2Pix) for MRI-only prostate …
[HTML][HTML] The use of MR-guided radiation therapy for head and neck cancer and recommended reporting guidance
BA McDonald, R Dal Bello, CD Fuller… - Seminars in radiation …, 2024 - Elsevier
Although magnetic resonance imaging (MRI) has become standard diagnostic workup for
head and neck malignancies and is currently recommended by most radiological societies …
head and neck malignancies and is currently recommended by most radiological societies …
Synthesis of pseudo-CT images from pelvic MRI images based on an MD-CycleGAN model for radiotherapy
H Sun, Q Xi, R Fan, J Sun, K Xie, X Ni… - Physics in Medicine & …, 2022 - iopscience.iop.org
Objective. A multi-discriminator-based cycle generative adversarial network (MD-CycleGAN)
model is proposed to synthesize higher-quality pseudo-CT from MRI images. Approach. MRI …
model is proposed to synthesize higher-quality pseudo-CT from MRI images. Approach. MRI …