NDLI: A system for grading diabetic maculopathy severity level

Content Provider	Springer Nature Link
Author	Sarma, Kandarpa Kumar Nirmala, S. R. Sharma, Purabi
Copyright Year	2014
Abstract	Diabetic maculopathy is a disease that may affect central vision and lead to blindness in severe cases. In this direction, the proposed automated system for grading the severity level of diabetic maculopathy can assist the ophthalmologists in early detection and diagnosis of the disease. Presence of exudates in the macular region is an important indication of maculopathy. The macula is localized based on its distance and position with respect to the optic disc. The macular region is then divided into three concentric geometric windows. Based on the presence of exudates in a particular window, the severity level of maculopathy is identified. If exudates are present in the innermost region then it is classified as severe case. Presence of exudates in the outermost region is classified as mild case. The moderate case is the one with exudates present in the middle region. The proposed work has been tested on retinal images with different levels of maculopathy from different databases (DIARETDB0, Messidor, DIARETDB1) and images obtained from a local eye hospital. The proposed method achieves a sensitivity of 96.2 % in correctly grading the different stages of maculopathy.
Starting Page	1
Ending Page	9
Page Count	9
File Format	PDF
ISSN	21926662
Journal	Network Modeling Analysis in Health Informatics and Bioinformatics
Volume Number	3
Issue Number	1
e-ISSN	21926670
Language	English
Publisher	Springer Vienna
Publisher Date	2014-01-29
Publisher Place	Vienna
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Computational Biology/Bioinformatics Exudates Complex Networks Health Informatics Optic disc Bioinformatics Diabetic maculopathy
Content Type	Text
Resource Type	Article
Subject	Urology

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