Title :
A Modified Matched Filter With Double-Sided Thresholding for Screening Proliferative Diabetic Retinopathy
Author :
Zhang, Lei ; Li, Qin ; You, Jane ; Zhang, David
Author_Institution :
Dept. of Comput., Hong Kong Polytech. Univ., Kowloon, China
fDate :
7/1/2009 12:00:00 AM
Abstract :
The early diagnosis of proliferative diabetic retinopathy (PDR), a common complication of diabetes that damages the retina, is crucial to the protection of the vision of diabetes sufferers. The onset of PDR is signaled by the appearance of neovascular net. Such neovascular nets might be identified using retinal vessel extraction techniques. The commonly used matched filter methods often produce false positive detections of neovascular nets due to their proneness to detect nonline edges as well as lines. In this paper, we propose a modified matched filter for retinal vessel extraction that applies a local vessel cross-section analysis using double-sided thresholding to reduce false responses to nonlinear edges. Our proposed modified matched filters demonstrated higher true positive rate and lesser false detection than existing matched-filter-based schemes in vessel extraction.
Keywords :
blood vessels; diseases; edge detection; feature extraction; matched filters; medical image processing; double-sided thresholding; edge detection; false positive detection; modified matched filter; neovascular net; proliferative diabetic retinopathy; retinal damage; retinal vessel extraction technique; vessel cross-section analysis; vision protection; Matched filter; proliferative diabetic retinopathy (PDR); retinal image; vessel extraction; Algorithms; Databases, Factual; Diabetic Retinopathy; False Positive Reactions; Humans; Image Interpretation, Computer-Assisted; Normal Distribution; Retina; Retinal Neovascularization;
Journal_Title :
Information Technology in Biomedicine, IEEE Transactions on
DOI :
10.1109/TITB.2008.2007201