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Encoder-Weighted W-Net for Unsupervised Segmentation of Cervix Region in Colposcopy Images
SIMPLE SUMMARY: The cervix region segmentation significantly affects the accuracy of diagnosis when analyzing colposcopy. Detecting the cervix region requires manual, intensive, and time-consuming labor from a trained gynecologist. In this paper, we propose a deep learning-based automatic cervix reg...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9317688/ https://www.ncbi.nlm.nih.gov/pubmed/35884460 http://dx.doi.org/10.3390/cancers14143400 |