Computer-aided cataract detection using enhanced texture features on retro-illumination lens images

Xinting Gao*, Huiqi Li, Joo Hwee Lim, Tien Yin Wong

*Corresponding author for this work

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

28 Citations (Scopus)

Abstract

Cataract is a leading cause of blindness worldwide. Computer-aided cataract detection is two-fold significant. Firstly, it will be helpful in mass screening. Secondly, it can be used as the preprocessing step for computer-aided grading. In this paper, the enhanced texture feature is proposed based on the graders' expertise of cataract and the characteristics of the retro-illumination lens images. The statistics of the enhanced texture feature is used to train the linear discriminant analysis to detect the cataract. The accuracy of 84.8% is achieved on a clinical database that contains 4545 pairs of images. It demonstrates that the proposed method is promising for mass screening and as the preprocessing step for computer-aided grading.

Original languageEnglish
Title of host publicationICIP 2011
Subtitle of host publication2011 18th IEEE International Conference on Image Processing
Pages1565-1568
Number of pages4
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event2011 18th IEEE International Conference on Image Processing, ICIP 2011 - Brussels, Belgium
Duration: 11 Sept 201114 Sept 2011

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Conference

Conference2011 18th IEEE International Conference on Image Processing, ICIP 2011
Country/TerritoryBelgium
CityBrussels
Period11/09/1114/09/11

Keywords

  • computer-aided cataract detection
  • feature extraction
  • texture analysis

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