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Exploiting probability density function of deep convolutional autoencoders’ latent space for reliable COVID-19 detection on CT scans
We present a probabilistic method for classifying chest computed tomography (CT) scans into COVID-19 and non-COVID-19. To this end, we design and train, in an unsupervised manner, a deep convolutional autoencoder (DCAE) on a selected training data set, which is composed only of COVID-19 CT scans. On...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer US
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8867464/ https://www.ncbi.nlm.nih.gov/pubmed/35228777 http://dx.doi.org/10.1007/s11227-022-04349-y |