Automatic glaucoma classification using color fundus images based on convolutional neural networks and transfer learning
Autor/a
Gómez-Valverde, Juan J.
Antón López, Alfonso
Fatti, Gianluca
Liefers, Bart
Herranz, Alejandra
Santos, Andrés
Sánchez, Clara I.
Ledesma-Carbayo, María J.
Fecha de publicación
2019-02-01ISSN
2156-7085
Resumen
Glaucoma detection in color fundus images is a challenging task that requires expertise and years of practice. In this study we exploited the application of different Convolutional Neural Networks (CNN) schemes to show the influence in the performance of relevant factors like the data set size, the architecture and the use of transfer learning vs newly defined architectures. We also compared the performance of the CNN based system with respect to human evaluators and explored the influence of the integration of images and data collected from the clinical history of the patients. We accomplished the best performance using a transfer learning scheme with VGG19 achieving an AUC of 0.94 with sensitivity and specificity ratios similar to the expert evaluators of the study. The experimental results using three different data sets with 2313 images indicate that this solution can be a valuable option for the design of a computer aid system for the detection of glaucoma in large-scale screening programs.
Tipo de documento
Artículo
Versión del documento
Versión aceptada
Lengua
English
Materias (CDU)
61 - Medicina
617 - Cirugía. Ortopedia. Oftalmología
Palabras clave
Glaucoma
Ulls--Malalties
Ojos--Enfermedades
Eye--Diseases
Oftalmologia
Ophthalmology
Oftalmología
Páginas
22
Publicado por
Optical Society of America
Colección
10; 2
Publicado en
Biomedical Optics Express
Citación
Gómez-Valverde, Juan J.; Antón López, Alfonso; Fatti, Gianluca; Liefers, Bart; Herranz, Alejandra; Santos, Andrés; Sánchez, Clara I.; Ledesma-Carbayo, María J. «Automatic glaucoma classification using color fundus images based on convolutional neural networks and transfer learning». Biomedical Optics Express, 2019, vol. 10, núm. 2, p. 892-913. Disponible en: <https://www.osapublishing.org/boe/abstract.cfm?uri=boe-10-2-892>. Fecha de acceso: 26 sept. 2019. DOI: https://doi.org/10.1364/BOE.10.000892
Este ítem aparece en la(s) siguiente(s) colección(ones)
- Ciències de la Salut [740]
Derechos
http://creativecommons.org/licenses/by-nc-nd/4.0/
Excepto si se señala otra cosa, la licencia del ítem se describe como http://creativecommons.org/licenses/by-nc-nd/4.0/