Deep learning‐based auto segmentation using generative adversarial network on magnetic resonance images obtained for head and neck cancer patients

PURPOSE: Adaptive radiotherapy requires auto‐segmentation in patients with head and neck (HN) cancer. In the current study, we propose an auto‐segmentation model using a generative adversarial network (GAN) on magnetic resonance (MR) images of HN cancer for MR‐guided radiotherapy (MRgRT). MATERIAL A...

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Detalles Bibliográficos
Autores principales: Kawahara, Daisuke, Tsuneda, Masato, Ozawa, Shuichi, Okamoto, Hiroyuki, Nakamura, Mitsuhiro, Nishio, Teiji, Nagata, Yasushi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Radiation Oncology Physics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9121028/
https://www.ncbi.nlm.nih.gov/pubmed/35263027
http://dx.doi.org/10.1002/acm2.13579

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9121028/
https://www.ncbi.nlm.nih.gov/pubmed/35263027
http://dx.doi.org/10.1002/acm2.13579

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