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Improvements in retinal vessel clustering techniques: Towards the automatic computation of the arterio venous ratio. (English) Zbl 1200.92025

Summary: The retinal blood vessel structure is an important indicator for diagnosis of several diseases, such as diabetes, hypertension, arteriosclerosis, or stroke. These pathologies cause early alterations in the blood vessels that affect veins and arteries differently. In this sense, the arterio venous ratio is a measurement that evaluates these alterations and, consequently, the condition of the patient. Thus, a precise identification of both types of vessels is necessary in order to develop an automatic diagnosis system, to quantify the seriousness of disease, or to monitor the therapy. The classification of vessels into veins and arteries is difficult due to the inhomogeneity in the retinal image lightness and the similarity of both structures. In this paper, several image feature sets have been combined with three clustering strategies in order to find a suitable characterization methodology. The best strategy has managed to classify correctly the 86.34% of the vessels improving the results obtained with previous techniques.

MSC:

92C50 Medical applications (general)
92C55 Biomedical imaging and signal processing
62H30 Classification and discrimination; cluster analysis (statistical aspects)
68T10 Pattern recognition, speech recognition
62P10 Applications of statistics to biology and medical sciences; meta analysis

Software:

WEKA
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Full Text: DOI

References:

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