Indirect deformable image registration using synthetic image generated by unsupervised deep learning-Reference-Cited by-同舟云学术

Indirect deformable image registration using synthetic image generated by unsupervised deep learning

Published:2024-08 Issue: Volume:148 Page:105143
ISSN:0262-8856
Container-title:Image and Vision Computing
language:en
Short-container-title:Image and Vision Computing

Author:

Hémon Cédric,Texier Blanche,Chourak Hilda,Simon Antoine,Bessières Igor,de Crevoisier Renaud,Castelli Joël,Lafond Caroline,Barateau Anaïs,Nunes Jean-Claude

Publisher

Elsevier BV

Reference53 articles.

1. Tracking the dose distribution in radiation therapy by accounting for variable anatomy;Schaly;Phys. Med. Biol.,2004

2. Contour-guided deep learning based deformable image registration for dose monitoring during cbct-guided radiotherapy of prostate cancer;Hemon;J. Appl. Clin. Med. Phys.,2023

3. Computed tomography synthesis from magnetic resonance imaging using cycle generative adversarial networks with multicenter learning;Texier;Phys. Imag. Radiat. Oncol.,2023

4. Deep learning based synthetic-ct generation in radiotherapy and pet: a review;Spadea;Med. Phys.,2021

5. Deep learning methods to generate synthetic CT from MRI in radiotherapy: a literature review;Boulanger;Phys. Med.,2021

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