Synthetic CT generation from cone-beam CT using deep-learning for breast adaptive radiotherapy - ScienceDirect

Evaluating synthetic computed tomography images for adaptive radiotherapy decision making in head and neck cancer - ScienceDirect

Cone-beam CT image quality improvement using Cycle-Deblur consistent adversarial networks (Cycle-Deblur GAN) for chest CT imaging in breast cancer patients

Deep learning in Radiotherapy

Cancers, Free Full-Text

Generating synthetic CT from low-dose cone-beam CT by using generative adversarial networks for adaptive radiotherapy, Radiation Oncology

PDF) Synthetic CT generation from cone-beam CT using deep-learning for breast adaptive radiotherapy

A cycle generative adversarial network for improving the quality of four-dimensional cone-beam computed tomography images, Radiation Oncology

Pipeline of the proposed scheme for generating synthetic CT. (a) Stage

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

Synthetic CT generation from CBCT images via deep learning. - Abstract - Europe PMC

Generating synthetic CT from low-dose cone-beam CT by using generative adversarial networks for adaptive radiotherapy, Radiation Oncology

Frontiers Geometric and Dosimetric Evaluation of Deep Learning-Based Automatic Delineation on CBCT-Synthesized CT and Planning CT for Breast Cancer Adaptive Radiotherapy: A Multi-Institutional Study