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...
| Publicado en: | Journal of Digital Imaging Vol. 36; no. 4; pp. 1376 - 1390 |
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| Autores principales: | , , , , , , , , , |
| Formato: | diagnostic images equations & formulas research tables/charts Journal Article |
| Publicado: |
Springer Nature
Aug2023
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| Acceso en línea: | Ver este registro en EBSCOhost |