Retinal Vessel Diameter Measurement Using Unsupervised Linear Discriminant Analysis
Author(s) -
Dinesh Kumar,
Behzad Aliahmad,
Hao Hao
Publication year - 2012
Publication title -
isrn ophthalmology
Language(s) - English
Resource type - Journals
eISSN - 2090-5696
pISSN - 2090-5688
DOI - 10.5402/2012/151369
Subject(s) - linear discriminant analysis , artificial intelligence , retinal , ground truth , computer science , cross section (physics) , pattern recognition (psychology) , mathematics , physics , biochemistry , chemistry , quantum mechanics
An automatic vessel diameter measurement technique based on linear discriminant analysis (LDA) has been proposed. After estimating the vessel wall, the vessel cross-section profile is divided into three regions: two corresponding to the background and one to the vessel. The algorithm was tested on more than 5000 cross-sections of retinal vessels from the REVIEW dataset through comparative study with the state-of-the-art techniques. Cross-correlation analyses were performed to determine the degree to which the proposed technique was close to the ground truth. The results indicate that proposed algorithm consistently performed better than most of other techniques and was highly correlated with the manual measurement as the reference diameter. The proposed method does not require any supervision and is suitable for automatic analysis.
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