IEEE Transactions on Medical Imaging · 2004 · 257 citations · 35 references
ComputingBiomedical EngineeringOphthalmologyBiomedical ImagingComputer VisionDiagnostic ImagingDiabetic RetinopathyDiameter MeasurementMedical Image AnalysisRetinal ImagingRetinal Vascular DiseaseShape AnalysisAutomated Image AnalysisAutomated Retinal Image AnalysisRetinal Image ProcessingRetinal Vessel AnalysisRetinal Vessel ImagingVascular Caliber AnalysisVessel Quantification
Changes in retinal vessel diameter are an important sign of diseases such as hypertension, arteriosclerosis and diabetes mellitus. Obtaining precise measurements of vascular widths is a critical and demanding process in automated retinal image analysis as the typical vessel is only a few pixels wide. This paper presents an algorithm to measure the vessel diameter to subpixel accuracy. The diameter measurement is based on a two-dimensional difference of Gaussian model, which is optimized to fit a two-dimensional intensity vessel segment. The performance of the method is evaluated against Brinchmann-Hansen's half height, Gregson's rectangular profile and Zhou's Gaussian model. Results from 100 sample profiles show that the presented algorithm is over 30% more precise than the compared techniques and is accurate to a third of a pixel.
35
Neural networks for pattern recognition
Choice Reviews Online · 1994 · 18.7K citations
Fundus Photographic Risk Factors for Progression of Diabetic Retinopathy
Ophthalmology · 1991 · 820 citations