NDLI: Automatic opacity detection in retro-illumination images for cortical cataract diagnosis

Content Provider	IEEE Xplore Digital Library
Author	Huiqi Li Liling Ko Joo Hwee Lim Jiang Liu Wong, D.W.K. Tien Yin Wong Ying Sun
Copyright Year	2008
Description	Author affiliation: Inst. for Infocomm Res., Agency for Sci., Technol. & Res., Singapore (Huiqi Li; Liling Ko; Joo Hwee Lim; Jiang Liu; Wong, D.W.K.)
Abstract	Computer aided analysis of medical images, a unique type of non-text media, can facilitate clinical diagnosis. As an example, an automatic opacity detection approach is proposed in this paper to grade cortical cataract more objectively. The automatic pupil detection is performed by detecting the strongest edges on the convex hull and ellipse fitting using nonlinear least square method. The cortical opacity is detected by radial edge detection and post-processing. The automatic grades are assigned following Wisconsin cataract grading protocol. The accuracy of pupil detection is 98.2%. The mean error of opacity area detection is 7 percent compared with the result of human grader. And 86.3% accurate grades of cortical cataract are achieved. This is the first time that the spoke-like feature is utilized in the automatic detection of cortical cataract to separate from other opacity types. The encouraging results show that it is probable to apply the proposed approach to clinical diagnosis later.
Starting Page	553
Ending Page	556
File Size	1356721
Page Count	4
File Format	PDF
ISBN	9781424425709
DOI	10.1109/ICME.2008.4607494
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-06-23
Publisher Place	Germany
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image edge detection Lenses Fitting Medical diagnostic imaging Biomedical imaging Noise Feature extraction cortical cataract medical image opacity detection
Content Type	Text
Resource Type	Article

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