A generative flow-based model for volumetric data augmentation in 3D deep learning for computed tomographic colonography

PURPOSE: Deep learning can be used for improving the performance of computer-aided detection (CADe) in various medical imaging tasks. However, in computed tomographic (CT) colonography, the performance is limited by the relatively small size and the variety of the available training datasets. Our pu...

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Detalles Bibliográficos
Autores principales: Uemura, Tomoki, Näppi, Janne J., Ryu, Yasuji, Watari, Chinatsu, Kamiya, Tohru, Yoshida, Hiroyuki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2020
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7822776/
https://www.ncbi.nlm.nih.gov/pubmed/33150471
http://dx.doi.org/10.1007/s11548-020-02275-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7822776/
https://www.ncbi.nlm.nih.gov/pubmed/33150471
http://dx.doi.org/10.1007/s11548-020-02275-z

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