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Title of Journal: J Med Syst

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Abbravation: Journal of Medical Systems

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Springer US

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DOI

10.1007/bf00484415

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ISSN

1573-689X

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Identification of Cataract and Postcataract Surge

Authors: Rajendra Udyavara Acharya Wenwei Yu Kuanyi Zhu Jagadish Nayak TeikCheng Lim Joey Yiptong Chan
Publish Date: 2009/05/09
Volume: 34, Issue: 4, Pages: 619-628
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Abstract

Human eyes are most sophisticated organ with perfect and interrelated subsystems such as retina pupil iris cornea lens and optic nerve The eye disorder such as cataract is a major health problem in the old age Cataract is formed by clouding of lens which is painless and developed slowly over a long period Cataract will slowly diminish the vision leading to the blindness At an average age of 65 it is most common and one third of the people of this age in world have cataract in one or both the eyes A system for detection of the cataract and to test for the efficacy of the postcataract surgery using optical images is proposed using artificial intelligence techniques Images processing and Fuzzy Kmeans clustering algorithm is applied on the raw optical images to detect the features specific to three classes to be classified Then the backpropagation algorithm BPA was used for the classification In this work we have used 140 optical image belonging to the three classes The ANN classifier showed an average rate of 933 in detecting normal cataract and post cataract optical images The system proposed exhibited 98 sensitivity and 100 specificity which indicates that the results are clinically significant This system can also be used to test the efficacy of the cataract operation by testing the postcataract surgery optical images


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