DocumentCode :
2018306
Title :
Measuring morphologic properties of the human retinal vessel system using a two-stage image processing approach
Author :
Kaupp, A. ; Dölemeyer, A. ; Wilzeck, R. ; Schlösser, R. ; Wolf, S. ; Meyer-Ebrecht, D.
Author_Institution :
Inst. for Meas. Technol., Aachen Univ. of Technol., Germany
Volume :
1
fYear :
1994
fDate :
13-16 Nov 1994
Firstpage :
431
Abstract :
The scanning laser technique in combination with digital image analysis can be used to assess the morphology of the retinal vascular tree. Quantitative description of the retinal vascular network may provide further knowledge in pathophysiology of retinal and systemic vascular disease. Especially, for monitoring of vascular alteration in follow-up studies quantitative reproducible methods to assess the vascular morphology are essential. Therefore we developed an automatic scheme allowing the measurement of morphological properties for the use in diagnosis and therapy control. To extract the morphological properties of the retina a two-stage image analysis procedure is employed. First the image is segmented in objects using a model-based top-down, image segmentation scheme. Then the obtained objects are classified with a neural net, the result being the tree of the arteries and veins. The third step is a measurement process which yields the desired information of arterial diameter, tortuosity and other morphological properties. As an example we show a functional image of the diameters and present a pilot-study in patients with arterial hypertension to demonstrate the ability of the new method for computerized analysis of the retinal vascular tree to detect arteriolar vascular alterations
Keywords :
blood flow measurement; blood pressure measurement; eye; image classification; image segmentation; mathematical morphology; medical image processing; neural nets; patient diagnosis; patient monitoring; arterial diameter; arterial hypertension; arteries; automatic measurement; diagnosis; digital image analysis; human retinal vessel system; image segmentation; morphologic properties measurement; neural net; pathophysiology; quantitative reproducible methods; retinal vascular disease; retinal vascular network; retinal vascular tree; scanning laser technique; systemic vascular disease; therapy control; tortuosity; two-stage image analysis; two-stage image processing; veins; Digital images; Diseases; Humans; Image analysis; Image segmentation; Medical treatment; Monitoring; Morphology; Retina; Retinal vessels;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 1994. Proceedings. ICIP-94., IEEE International Conference
Conference_Location :
Austin, TX
Print_ISBN :
0-8186-6952-7
Type :
conf
DOI :
10.1109/ICIP.1994.413350
Filename :
413350
Link To Document :
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