CCS-GAN: COVID-19 CT Scan Generation and Classification with Very Few Positive Training Images

We present a novel algorithm that is able to generate deep synthetic COVID-19 pneumonia CT scan slices using a very small sample of positive training images in tandem with a larger number of normal images. This generative algorithm produces images of sufficient accuracy to enable a DNN classifier to...

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Detalles Bibliográficos
Autores principales: Menon, Sumeet, Mangalagiri, Jayalakshmi, Galita, Josh, Morris, Michael, Saboury, Babak, Yesha, Yaacov, Yesha, Yelena, Nguyen, Phuong, Gangopadhyay, Aryya, Chapman, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10109233/
https://www.ncbi.nlm.nih.gov/pubmed/37069451
http://dx.doi.org/10.1007/s10278-023-00811-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10109233/
https://www.ncbi.nlm.nih.gov/pubmed/37069451
http://dx.doi.org/10.1007/s10278-023-00811-2

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