Computerized systems for cataract grading

Huiqi Li, Joo Hwee Lim, Jiang Liu, Damon Wing Kee Wong, Ngan Meng Tan, Shijian Lu, Zhuo Zhang, Tien Yin Wong

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationProceedings of the 2009 2nd International Conference on Biomedical Engineering and Informatics, BMEI 2009
DOIs
Publication statusPublished - 2009
Externally publishedYes
Event2009 2nd International Conference on Biomedical Engineering and Informatics, BMEI 2009 - Tianjin, China
Duration: 17 Oct 200919 Oct 2009

Publication series

NameProceedings of the 2009 2nd International Conference on Biomedical Engineering and Informatics, BMEI 2009

Conference

Conference2009 2nd International Conference on Biomedical Engineering and Informatics, BMEI 2009
Country/TerritoryChina
CityTianjin
Period17/10/0919/10/09

Keywords

  • Automatic diagnosis
  • Cortical cataract
  • Nuclear cataract

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

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