DocumentCode :
787450
Title :
Retinal vascular tree morphology: a semi-automatic quantification
Author :
Martinez-Perez, M. Elena ; Highes, A.D. ; Stanton, Alice V. ; Thorn, S.A. ; Chapman, Neil ; Bharath, Anil A. ; Parker, Kim H.
Author_Institution :
Dept. of Comput. Sci., Univ. Nacional Autonoma de Mexico, Mexico City, Mexico
Volume :
49
Issue :
8
fYear :
2002
Firstpage :
912
Lastpage :
917
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 :
angular measurement; area measurement; blood vessels; eye; image segmentation; image thinning; length measurement; medical image processing; optical images; binary images; chain code; clinical fundus images; crossing points; ff branch; geometrical properties; hypertensive subjects; normotensive subjects; retinal vascular tree morphology; semiautomatic quantification; thinning; topological properties; vascular geometry; vascular topology; vascular tree morphology; Area measurement; Biomedical imaging; Biomedical measurements; Blood vessels; Diseases; Geometry; Image processing; Image segmentation; Morphology; Retina; Adult; Algorithms; Female; Fluorescein Angiography; Humans; Hypertension; Image Processing, Computer-Assisted; Male; Middle Aged; Models, Cardiovascular; Pilot Projects; Retinal Vessels;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/TBME.2002.800789
Filename :
1019455
Link To Document :
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