Computer aided diagnosis of nuclear cataract

Huiqi Li, Hwee Lim Joo, Jiang Liu, Damon Wing Kee Wong, T. Y. Wong

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

3 Citations (Scopus)

Abstract

An approach to automatically diagnose nuclear cataract based on the slit-lamp image is proposed in this paper. Model-based approach is investigated to detect robust lens structure. Based on the detected lens structure, the mean intensity, the color information on the posterior subcapsular reflex and visual axis profile are extracted as the grading features. Support Vector Machine (SVM) regression model is further trained to predict the grades of nuclear cataract automatically. The proposed approach was tested using 900 images and the mean grading error is 0.36. The encouraging results show that it is promising to apply the proposed approach to clinical diagnosis.

Original languageEnglish
Title of host publication2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008
Pages1841-1844
Number of pages4
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008 - Singapore, Singapore
Duration: 3 Jun 20085 Jun 2008

Publication series

Name2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008

Conference

Conference2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008
Country/TerritorySingapore
CitySingapore
Period3/06/085/06/08

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Industrial and Manufacturing Engineering

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