Identificación de Neoplasia Intraepitelial Cervical para la predicción de Cáncer Cervical mediante el uso de aprendizaje profundo

The imaging diagnostic processes have developed high efficiency, gaining impact in the present day. However there are limits in their interpretation; That is the case of the Cervical Intraepithelial Neoplasia or cervical dysplasia. There are a lot of women worldwide suffering this lesion, in many patients their lives are not in danger, but there are other cases which the lesion evolves in one of the top 5 cancer with the higher mortality, the cervical cancer. Usually, the dysplasia is diagnosed by colposcopy, this method allows the lesion identification and the severity level within; But it is limited by the tissue complexity and in special cases, the specialists lack of experience driving the diagnostic. Meanwhile in developed countries, this issues are not common, it is important to develop diagnostic assistance technologies for the regions who need it. The investigations purpose is the use of classification deep learning models to predict the lesion presence and its severity in colposcopy images.

• Autores: Tenjo, Camilo Antonio
• Tipo de recurso: Trabajo de grado de pregrado
• Fecha de publicación: 2021
• Institución: Escuela Colombiana de Ingeniería Julio Garavito
• Repositorio: Repositorio Institucional ECI
• Idioma: spa
• OAI Identifier: oai:repositorio.escuelaing.edu.co:001/1933
• Acceso en línea: https://repositorio.escuelaing.edu.co/handle/001/1933; https://catalogo.escuelaing.edu.co/cgi-bin/koha/opac-detail.pl?biblionumber=22823
• Palabra clave: Aprendizaje profundo; Colposcopía; Modelo de Clasificación; Neoplasia Cervical Intraepitelial; Aprendizaje profundo; Colposcopía; Modelo de Clasificación; Neoplasia Cervical Intraepitelial; Deep learning; Colposcopy; Classification model; Cervical Intraepithelial Neoplasia
• Rights: openAccess
• License: http://purl.org/coar/access_right/c_abf2