Abstract

A semi-automatic method to measure and quantify geometrical and topological properties of continuous vascular trees in clinical fundus images is described. Measurements are made from binary images obtained with a previously described segmentation process. The skeletons of the segmented trees are produced by thinning,ff branch and crossing points are identified and segments of the trees are labeled and stored as a chain code. The operator selects a tree to be measured and decides if it is an arterial or venous tree. An automatic process then measures the lengths, areas and angles of the individual segments of the tree. Geometrical data and the connectivity information between branches from continuous retinal vessel trees are tabulated. A number of geometrical properties and topological indexes are derived. Vessel diameters and branching angles are validated against manual measurements and several derived geometrical and topological properties are extracted from red-free fundus images of ten normotensive and ten age- and sex-matched hypertensive subjects and compared with previously reported results.

Keywords

Tree (set theory)Mathematical morphologySegmentationBinary treeMedial axisFundus (uterus)Branching (polymer chemistry)Tree structureImage segmentationArtificial intelligenceComputer sciencePattern recognition (psychology)MathematicsImage processingComputer visionCombinatoricsAlgorithmImage (mathematics)Materials scienceMedicineOphthalmology

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Publication Info

Year
2002
Type
article
Volume
49
Issue
8
Pages
912-917
Citations
240
Access
Closed

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M. Elena Martínez-Pérez, A.D. Highes, Alice Stanton et al. (2002). Retinal vascular tree morphology: a semi-automatic quantification. IEEE Transactions on Biomedical Engineering , 49 (8) , 912-917. https://doi.org/10.1109/tbme.2002.800789

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DOI
10.1109/tbme.2002.800789