Una revisión sistemática de métodos de aprendizaje profundo aplicados a imágenes oculares

  • Oscar Julian Perdomo Charry Universidad del Rosario
  • Fabio Augusto González Osorio Universidad Nacional de Colombia
Palabras clave: hallazgos clínicos, enfermedades oculares, bases de datos oculares, aprendizaje profundo, diagnóstico clínico

Resumen

La inteligencia artificial está teniendo un importante impacto en diversas áreas de la medicina y a la oftalmología no ha sido la excepción. En particular, los métodos de aprendizaje profundo han sido aplicados con éxito en la detección de signos clínicos y la clasificación de enfermedades oculares. Esto representa un potencial impacto en el incremento de pacientes correctamente y oportunamente diagnosticados. En oftalmología, los métodos de aprendizaje profundo se han aplicado principalmente a imágenes de fondo de ojo y tomografía de coherencia óptica. Por un lado, estos métodos han logrado un rendimiento sobresaliente en la detección de enfermedades oculares tales como: retinopatía diabética, glaucoma, degeneración macular diabética y degeneración macular relacionada con la edad. Por otro lado, varios desafíos mundiales han compartido grandes conjuntos de datos con segmentación de parte de los ojos, signos clínicos y el diagnóstico ocular realizado por expertos. Adicionalmente, estos métodos están rompiendo el estigma de los modelos de caja negra, con la entrega de información clínica interpretable. Esta revisión proporciona una visión general de los métodos de aprendizaje profundo de última generación utilizados en imágenes oftálmicas, bases de datos y posibles desafíos para los diagnósticos oculares

Biografía del autor/a

Oscar Julian Perdomo Charry, Universidad del Rosario

Electronic Engineer, PhD (c) Systems and Computing Engineering, Assistant professor Universidad del Rosario Bogotá, Colombia.

Fabio Augusto González Osorio, Universidad Nacional de Colombia

Fabio Augusto González Systems Engineer, PhD Computer Science, Full Professor Universidad Nacional de Colombia Bogotá, Colombia.

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Biografía del autor/a

Oscar Julian Perdomo Charry, Universidad del Rosario

Electronic Engineer, PhD (c) Systems and Computing Engineering, Assistant professor Universidad del Rosario Bogotá, Colombia.

Fabio Augusto González Osorio, Universidad Nacional de Colombia

Fabio Augusto González Systems Engineer, PhD Computer Science, Full Professor Universidad Nacional de Colombia Bogotá, Colombia.

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Cómo citar
Perdomo Charry, O. J., & González Osorio, F. A. (2019). Una revisión sistemática de métodos de aprendizaje profundo aplicados a imágenes oculares. Ciencia E Ingeniería Neogranadina, 30(1), 9-26. https://doi.org/10.18359/rcin.4242
Publicado
2019-11-12
Sección
Artículos