Stable polyp-scene classification via subsampling and residual learning from an imbalanced large dataset

This Letter presents a stable polyp-scene classification method with low false positive (FP) detection. Precise automated polyp detection during colonoscopies is essential for preventing colon-cancer deaths. There is, therefore, a demand for a computer-assisted diagnosis (CAD) system for colonoscopi...

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Detalles Bibliográficos
Autores principales: Itoh, Hayato, Roth, Holger, Oda, Masahiro, Misawa, Masashi, Mori, Yuichi, Kudo, Shin-Ei, Mori, Kensaku
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Institution of Engineering and Technology 2019
Materias:
Special Issue: Papers from the 13th Workshop on Augmented Environments for Computer Assisted Interventions
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6952261/
https://www.ncbi.nlm.nih.gov/pubmed/32038864
http://dx.doi.org/10.1049/htl.2019.0079

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6952261/
https://www.ncbi.nlm.nih.gov/pubmed/32038864
http://dx.doi.org/10.1049/htl.2019.0079

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