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Proceedings Paper

Detection of retinal changes from illumination normalized fundus images using convolutional neural networks
Author(s): Kedir M. Adal; Peter G. van Etten; Jose P. Martinez; Kenneth Rouwen; Koenraad A. Vermeer; Lucas J. van Vliet
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Paper Abstract

Automated detection and quantification of spatio-temporal retinal changes is an important step to objectively assess disease progression and treatment effects for dynamic retinal diseases such as diabetic retinopathy (DR). However, detecting retinal changes caused by early DR lesions such as microaneurysms and dot hemorrhages from longitudinal pairs of fundus images is challenging due to intra and inter-image illumination variation between fundus images. This paper explores a method for automated detection of retinal changes from illumination normalized fundus images using a deep convolutional neural network (CNN), and compares its performance with two other CNNs trained separately on color and green channel fundus images. Illumination variation was addressed by correcting for the variability in the luminosity and contrast estimated from a large scale retinal regions. The CNN models were trained and evaluated on image patches extracted from a registered fundus image set collected from 51 diabetic eyes that were screened at two different time-points. The results show that using normalized images yield better performance than color and green channel images, suggesting that illumination normalization greatly facilitates CNNs to quickly and correctly learn distinctive local image features of DR related retinal changes.

Paper Details

Date Published: 3 March 2017
PDF: 6 pages
Proc. SPIE 10134, Medical Imaging 2017: Computer-Aided Diagnosis, 101341N (3 March 2017); doi: 10.1117/12.2254342
Show Author Affiliations
Kedir M. Adal, Technische Univ. Delft (Netherlands)
Rotterdam Ophthalmic Institute (Netherlands)
Peter G. van Etten, The Rotterdam Eye Hospital (Netherlands)
Jose P. Martinez, The Rotterdam Eye Hospital (Netherlands)
Kenneth Rouwen, The Rotterdam Eye Hospital (Netherlands)
Koenraad A. Vermeer, Rotterdam Ophthalmic Institute (Netherlands)
Lucas J. van Vliet, Technische Univ. Delft (Netherlands)


Published in SPIE Proceedings Vol. 10134:
Medical Imaging 2017: Computer-Aided Diagnosis
Samuel G. Armato; Nicholas A. Petrick, Editor(s)

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