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Fully automatic algorithm for the analysis of vessels in the angiographic image of the eye fundus
- Source :
- BioMedical Engineering OnLine, Vol 11, Iss 1, p 35 (2012), BioMedical Engineering
- Publication Year :
- 2012
- Publisher :
- BMC, 2012.
-
Abstract
- 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.
- Subjects :
- Adult
lcsh:Medical technology
Computer science
Fundus Oculi
Biomedical Engineering
Decision tree
Image processing
Fundus (eye)
Tortuosity
Convolution
Biomaterials
Automation
Young Adult
Classifier (linguistics)
medicine
Image Processing, Computer-Assisted
Humans
Radiology, Nuclear Medicine and imaging
Computer vision
Fully automatic algorithm
Aged
Aged, 80 and over
Radiological and Ultrasound Technology
medicine.diagnostic_test
business.industry
Research
Angiography
General Medicine
Middle Aged
eye diseases
medicine.anatomical_structure
Angiographic image
lcsh:R855-855.5
Blood Vessels
Artificial intelligence
business
Algorithm
Algorithms
Optic disc
Subjects
Details
- Language :
- English
- Volume :
- 11
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- BioMedical Engineering OnLine
- Accession number :
- edsair.doi.dedup.....f80d83d58f2c01f53e4e7dd39ba18627