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IEEE Trans Biomed Eng. 2010 Jul;57(7):1690-8. doi: 10.1109/TBME.2010.2041454. Epub 2010 Feb 17.

A computer-aided diagnosis system of nuclear cataract.

Author information

1
Institute for Infocomm Research, Agency for Science, Technology and Research, Singapore 138632, Singapore. huiqili@i2r.a-star.edu.sg

Abstract

Cataracts are the leading cause of blindness worldwide, and nuclear cataract is the most common form of cataract. An algorithm for automatic diagnosis of nuclear cataract is investigated in this paper. Nuclear cataract is graded according to the severity of opacity using slit lamp lens images. Anatomical structure in the lens image is detected using a modified active shape model. On the basis of the anatomical landmark, local features are extracted according to clinical grading protocol. Support vector machine regression is employed for grade prediction. This is the first time that the nucleus region can be detected automatically in slit lamp images. The system is validated using clinical images and clinical ground truth on >5000 images. The success rate of structure detection is 95% and the average grading difference is 0.36 on a 5.0 scale. The automatic diagnosis system can improve the grading objectivity and potentially be used in clinics and population studies to save the workload of ophthalmologists.

PMID:
20172776
DOI:
10.1109/TBME.2010.2041454
[Indexed for MEDLINE]

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