Retinal vascular tree morphology: a semi-automatic quantification.
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.
Martinez-Perez
M Elena
ME
Department of Computer Science, Institute of Research in Applied Mathematics and Systems (IIMAS), Universidad Nacional Autonoma de Mexico, Circuito Escolar Ciudad Universitaria, México, DF. elena@leibniz.iimas.unam.mx
Hughes
Alun D
AD
Stanton
Alice V
AV
Thom
Simon A
SA
Chapman
Neil
N
Bharath
Anil A
AA
Parker
Kim H
KH
D000328:Adult; D000465:Algorithms; D005260:Female; D005451:Fluorescein Angiography / Q000379:methods; D006801:Humans; D006973:Hypertension / Q000175:diagnosis* / Q000503:physiopathology; D007091:Image Processing, Computer-Assisted / Q000379:methods; D008297:Male; D008875:Middle Aged; D008955:Models, Cardiovascular; D010865:Pilot Projects; D012171:Retinal Vessels / Q000033:anatomy & histology* / Q000473:pathology