DocumentCode
2781695
Title
Automatic grading of diabetic maculopathy severity levels
Author
Siddalingaswamy, P.C. ; Prabhu, Gopalakrishna K.
Author_Institution
Dept. of Comput. Sci. & Eng., Manipal Univ., Manipal, India
fYear
2010
fDate
16-18 Dec. 2010
Firstpage
331
Lastpage
334
Abstract
Diabetic maculopathy is the major cause of irreversible vision loss due to retinopathy and is found in 10% of the world diabetic population. Compulsory mass screening will help to identify the maculopathy at early stage and reduce the risk of severe vision loss. In this paper, we present a computer based system for automatic detection and grading of diabetic maculopathy severity level without manual intervention. The optic disc is detected automatically and its location and diameter is used to detect fovea and to mark the macular region respectively. Next, hard exudates are detected using clustering and mathematical morphological techniques. Based on the location of exudates in marked macular region the severity level of maculopathy is classified into mild, moderate and severe. The method achieves a sensitivity of 95.6% and specificity of 96.15% with 148 retinal images for detecting maculopathy stages in fundus images as comparable to that of human expert.
Keywords
bio-optics; biomedical optical imaging; diseases; eye; medical image processing; pattern clustering; automatic detection; automatic grading; clustering techniques; compulsory mass screening; computer based system; detect fovea; diabetic maculopathy; diabetic maculopathy severity levels; human expert; irreversible vision loss; mathematical morphological techniques; optic disc; retinal images; Biomedical optical imaging; Diabetes; Optical imaging; Retina; Retinopathy; Sensitivity; Computer aided diagnosis; Diabetic maculopathy; exudates; optic disc;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems in Medicine and Biology (ICSMB), 2010 International Conference on
Conference_Location
Kharagpur
Print_ISBN
978-1-61284-039-0
Type
conf
DOI
10.1109/ICSMB.2010.5735398
Filename
5735398
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