Document Detail


Image based diagnosis of cortical cataract.
MedLine Citation:
PMID:  19163566     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
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.
Authors:
Huiqi Li; Liling Ko; Joo Hwee Lim; Jiang Liu; Damon Wing Kee Wong; Tien Yin Wong
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference     Volume:  2008     ISSN:  1557-170X     ISO Abbreviation:  Conf Proc IEEE Eng Med Biol Soc     Publication Date:  2008  
Date Detail:
Created Date:  2009-02-16     Completed Date:  2009-05-11     Revised Date:  2014-08-21    
Medline Journal Info:
Nlm Unique ID:  101243413     Medline TA:  Conf Proc IEEE Eng Med Biol Soc     Country:  United States    
Other Details:
Languages:  eng     Pagination:  3904-7     Citation Subset:  IM    
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MeSH Terms
Descriptor/Qualifier:
Algorithms
Cataract / classification,  diagnosis*
Diagnostic Techniques, Ophthalmological*
Humans
Image Processing, Computer-Assisted / standards*
Lens, Crystalline / anatomy & histology,  pathology*
Observer Variation
Pupil / physiology
Reproducibility of Results
Visual Acuity / physiology

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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