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...

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Detalles Bibliográficos
Autores principales: Park, Jinhee, Yang, Hyunmo, Roh, Hyun-Jin, Jung, Woonggyu, Jang, Gil-Jin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
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

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9317688/
https://www.ncbi.nlm.nih.gov/pubmed/35884460
http://dx.doi.org/10.3390/cancers14143400

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