@inproceedings{c699fb2ed1d04e7a861f3ea70d05ec23,
title = "Automatic opacity detection in retro-illumination images for cortical cataract diagnosis",
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 postprocessing. 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.",
keywords = "Cortical cataract, Medical image, Opacity detection",
author = "Huiqi Li and Liling Ko and Lim, {Joo Hwee} and Jiang Liu and Wong, {Damon Wing Kee} and Wong, {Tien Yin} and Ying Sun",
year = "2008",
doi = "10.1109/ICME.2008.4607494",
language = "English",
isbn = "9781424425716",
series = "2008 IEEE International Conference on Multimedia and Expo, ICME 2008 - Proceedings",
pages = "553--556",
booktitle = "2008 IEEE International Conference on Multimedia and Expo, ICME 2008 - Proceedings",
note = "2008 IEEE International Conference on Multimedia and Expo, ICME 2008 ; Conference date: 23-06-2008 Through 26-06-2008",
}