Vessel Boundary Delineation on Fundus Images Using Graph-Based Approach

• Published in: IEEE transactions on medical imaging Vol. 30; no. 6; pp. 1184 - 1191
• Main Authors: Xiayu Xu, Niemeijer, M, Qi Song, Sonka, M, Garvin, M K, Reinhardt, J M, Abramoff, M D
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.06.2011; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Biomedical imaging; Blood vessels; Boundaries; Delineation; Diabetic Retinopathy - pathology; Discs; Fluorescein Angiography - methods; Graph-based segmentation; Humans; Image edge detection; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; Image segmentation; Imaging, Three-Dimensional - methods; Observers; Pattern Recognition, Automated - methods; Pixel; Reproducibility of Results; Retina; retinal photography; Retinal Vessels - pathology; Retinoscopy - methods; Segmentation; Segments; Sensitivity and Specificity; vessel width measurement
• ISSN: 0278-0062; 1558-254X; 1558-254X
• DOI: 10.1109/TMI.2010.2103566

This paper proposes an algorithm to measure the width of retinal vessels in fundus photographs using graph-based algorithm to segment both vessel edges simultaneously. First, the simultaneous two-boundary segmentation problem is modeled as a two-slice, 3-D surface segmentation problem, which is further converted into the problem of computing a minimum closed set in a node-weighted graph. An initial segmentation is generated from a vessel probability image. We use the REVIEW database to evaluate diameter measurement performance. The algorithm is robust and estimates the vessel width with subpixel accuracy. The method is used to explore the relationship between the average vessel width and the distance from the optic disc in 600 subjects.