PubMed · 1997 · 78 citations · 5 references
Health ProfessionsOphthalmologyVision ScienceBiomedical ImagingComputer VisionMachine VisionMedical Image AnalysisOphthalmic ImagingOptical DiagnosticsRetinal AnatomyRetinal ExaminationRetinal ImagingAutomated MeasurementAutomated Retinal Image AnalysisBlood Vessel MorphologyRetinal Feature DetectionRetinal Image ProcessingRetinal Vessel Analysis
Automatic measurement of blood vessel tortuosity is a useful capability for automatic ophthalmological diagnostic tools. We describe a suite of automated tortuosity measures for blood vessel segments extracted from RGB retinal images. The tortuosity measures were evaluated in two classification tasks: (1) classifying the tortuosity of blood vessel segments and (2) classifying the tortuosity of blood vessel networks. These tortuosity measures were able to achieve a classification rate of 91% for the first problem and 95% on the second problem, which confirms that they capture much of the ophthalmologists' notion of tortuosity.
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