Local quality assessment of patient specific synthetic-CT via voxel-wise analysis-Reference-Cited by-同舟云学术

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Local quality assessment of patient specific synthetic-CT via voxel-wise analysis

Published:2022-11-30 Issue: Volume: Page:
ISSN:
Container-title:2022 International Conference on Digital Image Computing: Techniques and Applications (DICTA)
language:
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Author:

Chourak Hilda¹,Barateau Anaïs¹,Nunes Jean-Claude¹,Greer Peter B.²,Tahri Safaa¹,Lafond Caroline¹,de Crevoisier Renaud¹,Dowling Jason³,Acosta Oscar¹

Affiliation:

1. Univ Rennes, CLCC Eugè ne Marquis, INSERM, LTSI - UMR,Rennes,France,1099

2. School of Mathematical and Physical Sciences, University of Newcastle,Newcastle,New South Wales,Australia

3. The Australian eHealth Research Centre, CSIRO Health and Biosecurity,Brisbane,Queensland,Australia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10034558/10034559/10034622.pdf?arnumber=10034622

Reference30 articles.

1. Deep learning methods to generate synthetic CT from MRI in radiotherapy: A literature review

2. Deep learning based synthetic‐CT generation in radiotherapy and PET: A review

3. Image quality assessment

4. Evaluation of a deep learning-based pelvic synthetic CT generation technique for MRI-based prostate proton treatment planning

5. Medical Imaging: Image Processing - Supervised local error estimation for nonlinear image registration using convolutional neural networks;eppenhof;SPIE Proceedings,2017

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