Glaucoma Diagnosis from Eye Fundus Images Based on Deep Morphometric Feature Estimation

Oscar Perdomo, Vincent Andrearczyk, Fabrice Meriaudeau, Henning Müller, Fabio A. González

Resultado de la investigación: Capítulo en Libro/Reporte/ConferenciaCapítulo

8 Citas (Scopus)

Resumen

Glaucoma is an ophthalmic disease related to damage in the optic nerve and it is without symptoms in its early stages. Left untreated, it can lead to vision limitation and blindness. Eye fundus images have been widely accepted by medical personnel to examine the morphology and texture of the optic nerve head and the physiologic cup but glaucoma diagnosis is still subjective and without clear consensus among experts. This paper presents a multi-stage deep learning model for glaucoma diagnosis based on a curriculum learning strategy. In curriculum learning, a model is sequentially trained to solve incrementally difficult tasks. Our proposed model includes the following stages: segmentation of the optic disc and physiological cup, prediction of morphometric features from segmentations, and prediction of disease level (healthy, suspicious and glaucoma). The experimental evaluation shows that our proposed method outperforms conventional convolutional deep learning models from the state of the art reported on the RIM-ONE-v1 and DRISHTI-GS1 datasets with an accuracy of 89.4% and an AUC of 0.82 respectively.

Idioma originalInglés estadounidense
Título de la publicación alojadaComputational Pathology and Ophthalmic Medical Image Analysis - First International Workshop, COMPAY 2018, and 5th International Workshop, OMIA 2018, Held in Conjunction with MICCAI 2018, Proceedings
EditoresZeike Taylor, Hrvoje Bogunovic, David Snead, Mona K. Garvin, Xin Jan Chen, Francesco Ciompi, Yanwu Xu, Lena Maier-Hein, Mitko Veta, Emanuele Trucco, Danail Stoyanov, Nasir Rajpoot, Jeroen van der Laak, Anne Martel, Stephen McKenna
EditorialSpringer
Páginas319-327
Número de páginas9
ISBN (versión impresa)9783030009489
DOI
EstadoPublicada - 2018
Publicado de forma externa
Evento1st International Workshop on Computational Pathology, COMPAY 2018 and 5th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2018 Held in Conjunction with MICCAI 2018 - Granada, Espana
Duración: sep 16 2018sep 20 2018

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen11039 LNCS
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia1st International Workshop on Computational Pathology, COMPAY 2018 and 5th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2018 Held in Conjunction with MICCAI 2018
PaísEspana
CiudadGranada
Período9/16/189/20/18

All Science Journal Classification (ASJC) codes

  • Ciencia computacional teórica
  • Informática (todo)

Huella Profundice en los temas de investigación de 'Glaucoma Diagnosis from Eye Fundus Images Based on Deep Morphometric Feature Estimation'. En conjunto forman una huella única.

Citar esto