Publication | Closed Access
Automatic Segmentation of Blood Vessels in Retinal Image Based on Fuzzy K-Median Clustering
19
Citations
11
References
2007
Year
Unknown Venue
EngineeringRetinal ImageSegmentation ResultsBiomedical EngineeringImage AnalysisPattern RecognitionEdge DetectionFuzzy K-median ClusteringAutomatic SegmentationMachine VisionVascular ImageOphthalmologyMedical ImagingVisual DiagnosisVessel SegmentationMedical Image ComputingComputer VisionComputer-aided DiagnosisFuzzy ClusteringImage Segmentation
This paper presents an efficient method for automatic segmentation of blood vessels in retinal images. Specifically, we also delineate vascular intersections/crossovers. The proposed algorithm is composed of three steps: matched filter, fuzzy k-median (FKMED), and length filter. The segmentation results are compared with clinically generated vessel segmentation and are evaluated in terms of sensitivity and specificity. The results are encouraging and will be used for further application such as personal identification.
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