Improving synthetic CT accuracy by combining the benefits of multiple normalized preprocesses

PURPOSE: To investigate the effect of different normalization preprocesses in deep learning on the accuracy of different tissues in synthetic computed tomography (sCT) and to combine their advantages to improve the accuracy of all tissues. METHODS: The cycle‐consistent adversarial network (CycleGAN)...

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Detalles Bibliográficos
Autores principales: Cao, Zheng, Gao, Xiang, Chang, Yankui, Liu, Gongfa, Pei, Yuanji
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Radiation Oncology Physics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10402686/
https://www.ncbi.nlm.nih.gov/pubmed/37092739
http://dx.doi.org/10.1002/acm2.14004

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10402686/
https://www.ncbi.nlm.nih.gov/pubmed/37092739
http://dx.doi.org/10.1002/acm2.14004

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