Fully automatic algorithm for the analysis of vessels in the angiographic image of the eye fundus.
BACKGROUND
The available scientific literature contains descriptions of manual, semi-automated and automated methods for analysing angiographic images. The presented algorithms segment vessels calculating their tortuosity or number in a given area. We describe a statistical analysis of the inclination of the vessels in the fundus as related to their distance from the center of the optic disc.


METHODS
The paper presents an automated method for analysing vessels which are found in angiographic images of the eye using a Matlab implemented algorithm. It performs filtration and convolution operations with suggested masks. The result is an image containing information on the location of vessels and their inclination angle in relation to the center of the optic disc. This is a new approach to the analysis of vessels whose usefulness has been confirmed in the diagnosis of hypertension.


RESULTS
The proposed algorithm analyzed and processed the images of the eye fundus using a classifier in the form of decision trees. It enabled the proper classification of healthy patients and those with hypertension. The result is a very good separation of healthy subjects from the hypertensive ones: sensitivity - 83%, specificity - 100%, accuracy - 96%. This confirms a practical usefulness of the proposed method.


CONCLUSIONS
This paper presents an algorithm for the automatic analysis of morphological parameters of the fundus vessels. Such an analysis is performed during fluorescein angiography of the eye. The presented algorithm automatically calculates the global statistical features connected with both tortuosity of vessels and their total area or their number.
Department of Computer Biomedical Systems, Institute of Computer Science, University of Silesia, ul, Będzińska 39, 41-200, Sosnowiec, Poland. robert.koprowski@us.edu.pl
Robert
R
Koprowski
Sławomir Jan
SJ
Teper
Beata
B
Węglarz
Edward
E
Wylęgała
Michał
M
Krejca
Zygmunt
Z
Wróbel
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D000792:Angiography; D001331:Automation; D001808:Blood Vessels; D005654:Fundus Oculi; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008875:Middle Aged; D055815:Young Adult