@inproceedings{61efad1d6f8842f8ba18987d2d595219,
title = "Computerized systems for cataract grading",
abstract = "Cataract is the leading cause of blindness worldwide. Two automatic grading systems are presented in this paper for nuclear cataract and cortical cataract diagnosis respectively. Model-based approach was applied to detect anatomical structure in slit-lamp images. Features were extracted based on the lens structure and severity of nuclear cataract was predicted using Support Vector Machines (SVM) regression. For cortical cataract, the opacity was detected using region growing. The seeds were selected by local thresholding and edge detection in radial direction. Cortical cataract was graded based on the area of cortical opacity. Both of the systems were tested by clinical data and results show that the automatic systems can provide objective grading of cataracts.",
keywords = "Automatic diagnosis, Cortical cataract, Nuclear cataract",
author = "Huiqi Li and Lim, {Joo Hwee} and Jiang Liu and Wong, {Damon Wing Kee} and Tan, {Ngan Meng} and Shijian Lu and Zhuo Zhang and Wong, {Tien Yin}",
note = "Copyright: Copyright 2010 Elsevier B.V., All rights reserved.; 2009 2nd International Conference on Biomedical Engineering and Informatics, BMEI 2009 ; Conference date: 17-10-2009 Through 19-10-2009",
year = "2009",
doi = "10.1109/BMEI.2009.5304895",
language = "English",
isbn = "9781424441341",
series = "Proceedings of the 2009 2nd International Conference on Biomedical Engineering and Informatics, BMEI 2009",
booktitle = "Proceedings of the 2009 2nd International Conference on Biomedical Engineering and Informatics, BMEI 2009",
}