Antal, Bálint

Antal Bálint

University of Szeged

Approaches to Improve Macula Detection in Retinal ImagesBálint AntalDiabetic retinopathy (DR) is the most common cause of blindness in the developed coun-tries. The screening of this disease is currently done manually, nevertheless it is a very resourcedemanding procedure. Several efforts have been made to establish a computer-based auto-matic screening system. The basis of an automatic screening system is the analysis of retinalimages.The analysis consists of two parts: the detection of certain anatomical parts and the detectionof disorders caused by DR. In this paper, we present an approach which belongs to the firstcategory. Macula is the center of sharp vision, so disorders which appear within this anatomicalpart can lead to vision loss. That is, the proper detection of the macula is essential also for a DRscreening system to be able to classify lesions closer to the macula center as more dangerous.In this paper, we present a novel macula detector, which is competitive with the state-of-the-art methods (e. g. [1]). This approach is based on the fact that macula appears as a spot whichis darker than the surface of the retina. The algorithm can be summarized as follows:First, we extract the green plane from the color fundus image. We generate the backgroundimage by applying median filter and subtract it from the green plane, resulting in a shadecorrected image. Next, we binarize the image by considering all non-zero pixels as foregroundpixels, and others as background. Finally, we apply an image labeling procedure and select thelargest component as the macula.In addition, we present the effect of determining the parameter setup for the algorithmautomatically using a simulated annealing algorithm. We also determine the spatial bias ofthe algorithm, the correction of which leads to further improvement. We also show that thisalgorithm improves the accuracy of an ensemble-based system[2] which uses several maculadetectors.AcknowledgmentsThis work was supported in part by the János Bolyai grant of the Hungarian Academy of Sci-ences, and by the TECH08-2 project DRSCREEN - Developing a computer based image pro-cessing system for diabetic retinopathy screening of the National Office for Research and Tech-nology of Hungary (contract no.: OM-00194/2008, OM-00195/2008, OM-00196/2008). We alsoacknowledge the Moorefields Eye Hospital, London for their clinical support.References[1] S. Sekhar, W. Al-Nuaimy, A. K. Nandi, Automated localization of optic disc and fovea inretinal fundus images, 16th European Signal Processing Conference, Lausanne, Switzer-land, 5 pages, 2008.[2] B. Harangi, R.J. Qureshi, A. Csutak, T. Peto, A. Hajdu: Automatic detection of the opticdisc using majority voting in a collection of optic disc detectors, 7th IEEE InternationalSymposium on Biomedical Imaging (ISBI 2010), Rotterdam, The Netherlands, 2010, 1329-1332.12

Approaches to improve macula detection in retinal images : [abstract]

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Approaches to improve macula detection in retinal images

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