Negative Samples for Improving Object Detection—A Case Study in AI-Assisted Colonoscopy for Polyp Detection

Deep learning object-detection models are being successfully applied to develop computer-aided diagnosis systems for aiding polyp detection during colonoscopies. Here, we evidence the need to include negative samples for both (i) reducing false positives during the polyp-finding phase, by including...

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Detalles Bibliográficos
Autores principales: Nogueira-Rodríguez, Alba, Glez-Peña, Daniel, Reboiro-Jato, Miguel, López-Fernández, Hugo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10001273/
https://www.ncbi.nlm.nih.gov/pubmed/36900110
http://dx.doi.org/10.3390/diagnostics13050966

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10001273/
https://www.ncbi.nlm.nih.gov/pubmed/36900110
http://dx.doi.org/10.3390/diagnostics13050966

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