Computational learning of features for automated colonic polyp classification

Shape, texture, and color are critical features for assessing the degree of dysplasia in colonic polyps. A comprehensive analysis of these features is presented in this paper. Shape features are extracted using generic Fourier descriptor. The nonsubsampled contourlet transform is used as texture and...

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Detalles Bibliográficos
Autores principales: Bora, Kangkana, Bhuyan, M. K., Kasugai, Kunio, Mallik, Saurav, Zhao, Zhongming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7902635/
https://www.ncbi.nlm.nih.gov/pubmed/33623086
http://dx.doi.org/10.1038/s41598-021-83788-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7902635/
https://www.ncbi.nlm.nih.gov/pubmed/33623086
http://dx.doi.org/10.1038/s41598-021-83788-8

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