Sunday 21st of January 2018

Automatic Detection of Exudates in Retinal Images

Nidhal K. El Abbadi and Enas Hamood Al Saadi

Diabetic retinopathy is a major cause of blindness. Earliest signs of diabetic retinopathy are damage to blood vessels in the eye and then the formation of lesions in the retina. This paper presents an automated method for the detection of bright lesions (exudates) in retinal images. New methods are developed to localize and isolate the optic disk and detect the exudates. A novel algorithm presented to localize the optic disk and treat the confusion due to similarity between exudates and optic disk. The algorithm used specific color channels and some of image features to separate exudates from physiological features in digital fundus images. The algorithm is tested on many images from a published database and gives excellent and promise results.

Keywords: retina, optic disk, exudates, diabetic, retinopathy.

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Nidhal K. El Abbadi
Received BSc in chemical engineering, BSc, MSc, and PhD in computer science, worked in industry and many universities, he is general secretary of colleges of computing and informatics society in Iraq, Member of Editorial Board of Journal of Computing and Applications,reviewer for a number of international journals, has many published papers and three published books ( programming with Pascal, C++ from beginning to OOP, Data structures in simple language), his research interests are in image processing, biomedical, and steganography, Hes Associate Professor in Computer Science in the University of Kufa Najaf, IRAQ.

Enas Hamood Al Saadi
BSc., and MSc in Computer science from college of science / Babylon University. Currently PhD student in Computer science / college of science / Babylon University. Work as lecturer in college of education / Babylon University She has 6 researches in computer science fields

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