Automated detection of diabetic retinopathy in fundus images using fused features
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SCIENTIFIC PAPER
Automated detection of diabetic retinopathy in fundus images using fused features Iqra Bibi1 · Junaid Mir1 · Gulistan Raja1 Received: 6 January 2020 / Accepted: 14 September 2020 © Australasian College of Physical Scientists and Engineers in Medicine 2020
Abstract Diabetic retinopathy (DR) is one of the severe eye conditions due to diabetes complication which can lead to vision loss if left untreated. In this paper, a computationally simple, yet very effective, DR detection method is proposed. First, a segmentation independent two-stage preprocessing based technique is proposed which can effectively extract DR pathognomonic signs; both bright and red lesions, and blood vessels from the eye fundus image. Then, the performance of Local Binary Patterns (LBP), Local Ternary Patterns (LTP), Dense Scale-Invariant Feature Transform (DSIFT) and Histogram of Oriented Gradients (HOG) as a feature descriptor for fundus images, is thoroughly analyzed. SVM kernel-based classifiers are trained and tested, using a 5-fold cross-validation scheme, on both newly acquired fundus image database from the local hospital and combined database created from the open-sourced available databases. The classification accuracy of 96.6% with 0.964 sensitivity and 0.969 specificity is achieved using a Cubic SVM classifier with LBP and LTP fused features for the local database. More importantly, in out-of-sample testing on the combined database, the model gives an accuracy of 95.21% with a sensitivity of 0.970 and specificity of 0.932. This indicates the proposed model is very well-fitted and generalized which is further corroborated by the presented train-test curves. Keywords Diabetic retinopathy · Fundus images · CAD systems · Retinal image · Texture features
Introduction Eye conditions are becoming remarkably common nowadays, with a subsequent rise in the number of people with vision impairment over the past decade [1]. According to the recent World Health Organization (WHO) report [2], at least 2.2 billion people worldwide have a blindness or vision problem. More importantly, at least 1 billion people have an eye condition that was preventable or is yet to be treated. It is expected that the number of people with eye conditions will increase dramatically in the later years, mainly due to the aging, behavioral and lifestyle changes, and urbanization in the growing population [2]. Diabetic Retinopathy (DR) is one of the severe eye conditions due to diabetes complications in which high blood sugar levels damage the blood vessels in the retina. These damaged blood vessels begin to leak fluid and blood, resulting in the swelling of the central * Gulistan Raja [email protected] 1
Electrical Engineering Department, University of Engineering and Technology, Taxila, Pakistan
part of the retina, the macula, and may lead to severe vision impairment or blindness. The vision loss or severe eye conditions due to the onset and progression of DR can be generally avoided through early detection and timely treatment. Howe
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