A computer assisted method for nuclear cataract grading from slit-lamp images using ranking

Wei Huang, Kap Luk Chan, Huiqi Li, Joo Hwee Lim, Jiang Liu, Tien Yin Wong

Research output: Journal PublicationArticlepeer-review

41 Citations (Scopus)

Abstract

In clinical diagnosis, a grade indicating the severity of nuclear cataract is often manually assigned by a trained ophthalmologist to a patient after comparing the lens' opacity severity in his/her slit-lamp images with a set of standard photos. This grading scheme is often subjective and time-consuming. In this paper, a novel computer-aided diagnosis method via ranking is proposed to facilitate nuclear cataract grading following conventional clinical decision-making process. The grade of nuclear cataract in a slit-lamp image is predicted using its neighboring labeled images in a ranked image list, which is achieved using a learned ranking function. This ranking function is learned via direct optimization on a newly proposed approximation to a ranking evaluation measure. Our proposed method has been evaluated by a large dataset composed of 1000 different cases, which are collected from an ongoing clinical population-based study. Both experimental results and comparison with several existing methods demonstrate the benefit of grading via ranking by our proposed method.

Original languageEnglish
Article number5530401
Pages (from-to)94-107
Number of pages14
JournalIEEE Transactions on Medical Imaging
Volume30
Issue number1
DOIs
Publication statusPublished - Jan 2011
Externally publishedYes

Keywords

  • Computer-aided diagnosis (CAD)
  • grade
  • nuclear cataract
  • ranking
  • slit-lamp images

ASJC Scopus subject areas

  • Software
  • Radiological and Ultrasound Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering

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