Image based diagnosis of cortical cataract.

Published

Journal Article

An automatic approach to detect cortical opacities and grade the severity of cortical cataract from retro-illumination images is proposed. The spoke-like feature of cortical opacity is employed to separate from other opacity type. The proposed algorithms were tested by images from a community study. The success rate of region of interest (ROI) detection is 98.2% for 611 images. For 466 images tested, the mean error of opacity area detection is 3.15% compared with human grader and 85.6% of exact cortical cataract grading is obtained. The experimental results show that the proposed approach is promising in clinical diagnosis.

Full Text

Duke Authors

Cited Authors

  • Li, H; Ko, L; Lim, JH; Liu, J; Wong, DWK; Wong, TY

Published Date

  • 2008

Published In

Volume / Issue

  • 2008 /

Start / End Page

  • 3904 - 3907

PubMed ID

  • 19163566

Pubmed Central ID

  • 19163566

International Standard Serial Number (ISSN)

  • 1557-170X

Digital Object Identifier (DOI)

  • 10.1109/IEMBS.2008.4650063

Language

  • eng

Conference Location

  • United States