Kudo's classification for colon polyps assessment using a deep learning approach
| dc.contributor.author | Patiño Barrientos, Sebastián | |
| dc.contributor.author | Sierra-Sosa, Daniel | |
| dc.contributor.author | García-Zapirain, Begoña | |
| dc.contributor.author | Castillo Olea, Cristian | |
| dc.contributor.author | Elmaghraby, Adel Said | |
| dc.date.accessioned | 2026-03-18T12:14:18Z | |
| dc.date.available | 2026-03-18T12:14:18Z | |
| dc.date.issued | 2020-01-10 | |
| dc.date.updated | 2026-03-18T12:14:18Z | |
| dc.description.abstract | Colorectal cancer (CRC) is the second leading cause of cancer death in the world. This disease could begin as a non-cancerous polyp in the colon, when not treated in a timely manner, these polyps could induce cancer, and in turn, death. We propose a deep learning model for classifying colon polyps based on the Kudo's classification schema, using basic colonoscopy equipment. We train a deep convolutional model with a private dataset from the University of Deusto with and without using a VGG model as a feature extractor, and compared the results. We obtained 83% of accuracy and 83% of F1-score after fine tuning our model with the VGG filter. These results show that deep learning algorithms are useful to develop computer-aided tools for early CRC detection, and suggest combining it with a polyp segmentation model for its use by specialists. | en |
| dc.description.sponsorship | This research was supported by the Basque Government “Aids for health research projects” and the publication fees supported by the Basque Government Department of Education (eVIDA Certified Group IT905-16) | en |
| dc.identifier.citation | Patino-Barrientos, S., Sierra-Sosa, D., Garcia-Zapirain, B., Castillo-Olea, C., & Elmaghraby, A. (2020). Kudo’s classification for colon polyps assessment using a deep learning approach. Applied Sciences (Switzerland), 10(2). https://doi.org/10.3390/APP10020501 | |
| dc.identifier.doi | 10.3390/APP10020501 | |
| dc.identifier.eissn | 2076-3417 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14454/5515 | |
| dc.language.iso | eng | |
| dc.publisher | MDPI AG | |
| dc.rights | © 2020 by the authors. | |
| dc.subject.other | Colon cancer | |
| dc.subject.other | Deep learning | |
| dc.subject.other | Image processing | |
| dc.subject.other | Medical dataset | |
| dc.subject.other | VGG | |
| dc.title | Kudo's classification for colon polyps assessment using a deep learning approach | en |
| dc.type | journal article | |
| dcterms.accessRights | open access | |
| oaire.citation.issue | 2 | |
| oaire.citation.title | Applied Sciences (Switzerland) | |
| oaire.citation.volume | 10 | |
| oaire.licenseCondition | https://creativecommons.org/licenses/by/4.0/ | |
| oaire.version | VoR |
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