Automatic Diagnosis of Diabetic Retinopathy from Fundus Images Using Digital Signal and Image Processing Techniques

Document type: Conference Papers
Peer reviewed: Yes
Author(s): A.M. Aibinu, Muhammad Imran Iqbal, M. Nilsson, M.J.E. Salami
Title: Automatic Diagnosis of Diabetic Retinopathy from Fundus Images Using Digital Signal and Image Processing Techniques
Conference name: International Conference on Robotics, Vision, Information, and Signal Processing
Year: 2007
City: Penang, Malaysia
Organization: Blekinge Institute of Technology
Department: School of Engineering - Dept. of Signal Processing (Sektionen för teknik – avd. för signalbehandling)
School of Engineering S- 372 25 Ronneby
+46 455 38 50 00
http://www.tek.bth.se/
Authors e-mail: muhammad.imran.iqbal@bth.se
Language: English
Abstract: Automatic diagnosis and display of diabetic retinopathy from images of retina using the techniques of digital
signal and image processing is presented in this paper. The acquired images undergo pre-processing to equalize uneven illumination associated with the acquired fundus images. This stage also removes noise present in the image. Segmentation stage clusters the image into two distinct classes while the abnormalities detection stage was used to distinguish between candidate lesions and other information. Methods of diagnosis of red spots, bleeding and detection of vein-artery crossover points have also been developed in this work using the color information, shape, size, object length to breadth ration as contained in the acquired digital fundus image. Furthermore, two graphical user interfaces (GUIs) have also been developed during this work; the first is for the collection of lesion data information and was used by the ophthalmologist in marking images for database while the second GUI is for automatic diagnosing and displaying of the result in a user friendly manner. The algorithm was tested with a separate set of 25 fundus images. From this, the result obtained for microaneurysms and haemorrhages diagnosis shows the appropriateness of the method.
Subject: Signal Processing\Detection and Classification
Medical Sciences
Keywords: Diabetic Retinopathy, Fundus Image, Digital Image Processing, Segmentation, Retina, Classifier.
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