NDLI: Mobile cataract detection using optimal combination of statistical texture analysis

Content Provider	IEEE Xplore Digital Library
Author	Fuadah, Yunendah Nur Setiawan, Agung W. Mengko, Tati L.R. Budiman
Copyright Year	2015
Description	Author affiliation: Cicendo Eye Hospital, Bandung, Indonesia (Budiman) \|\| School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Indonesia (Fuadah, Yunendah Nur; Setiawan, Agung W.; Mengko, Tati L.R.)
Abstract	Cataract is one of potentially dangerous disease that will be causing the blindness as an impact of the belated in handling cataract. Cataract is not only disrupting productivity and mobility of patients, but also causing the social-economic impact that will decrease the quality of life. Early detection of cataract reputed as a principal arrangement in restraining the increasing number of blindness caused by cataract. Commonly, an ophthalmologist uses a slit lamp camera to diagnose a cataract. Lacking of ophthalmologist and slit lamp camera in rural areas are the main problem of the belated in diagnosing cataract. In this paper, we investigate the optimal combination candidate of statistical texture features that is provide highest accuracy for cataract detection. In this research, we use K-Nearest Neighbor (k-NN) as classification method that will be implemented on android smartphone. Our result show that the optimal combination of texture features are dissimilarity, contrast, and uniformity. The highest accuracy of the system is 97.5%. The system is implemented on mobile smartphone.
Starting Page	232
Ending Page	236
File Size	438091
Page Count	5
File Format	PDF
e-ISBN	9781467378000
DOI	10.1109/ICICI-BME.2015.7401368
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-11-02
Publisher Place	Indonesia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	K-NN Statistical texture analysis Correlation Symmetric matrices Cataract Optimal combination Training data Blindness Biomedical measurement Feature extraction Mobile Biomedical engineering
Content Type	Text
Resource Type	Article

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