期刊
IEEE TRANSACTIONS ON MEDICAL IMAGING
卷 37, 期 2, 页码 516-526出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TMI.2017.2762963
关键词
Retina; scanning laser ophthalmoscope; ultra-widefield; artery-vein classification; blood vessel; graph cut
类别
资金
- Optos plc, Dunfermline, U.K.
- EPSRC [EP/M005976/1] Funding Source: UKRI
- Engineering and Physical Sciences Research Council [EP/M005976/1] Funding Source: researchfish
The classification of blood vessels into arterioles and venules is a fundamental step in the automatic investigation of retinal biomarkers for systemic diseases. In this paper, we present a novel technique for vessel classification on ultra-wide-field-of-view images of the retinal fundus acquired with a scanning laser ophthalmoscope. To the best of our knowledge, this is the first time that a fully automated artery/vein classification technique for this type of retinal imaging with no manual intervention has been presented. The proposed method exploits hand-crafted features based on local vessel intensity and vascular morphology to formulate a graph representation from which a globally optimal separation between the arterial and venular networks is computed by graph cut approach. The technique was tested on three different data sets (one publicly available and two local) and achieved an average classification accuracy of 0.883 in the largest data set.
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