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Semi-supervised CycleGAN for domain transformation of chest CT images and its application to opacity classification of diffuse lung diseases

PURPOSE: The performance of deep learning may fluctuate depending on the imaging devices and settings. Although domain transformation such as CycleGAN for normalizing images is useful, CycleGAN does not use information on the disease classes. Therefore, we propose a semi-supervised CycleGAN with an...

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Detalles Bibliográficos
Autores principales:	Mabu, Shingo, Miyake, Masashi, Kuremoto, Takashi, Kido, Shoji
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Springer International Publishing 2021
Materias:	Original Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8522550/ https://www.ncbi.nlm.nih.gov/pubmed/34661818 http://dx.doi.org/10.1007/s11548-021-02490-2

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