Abstract
The detection of venous beading in retinal images provides an early sign of diabetic retinopathy and plays an important role as a preprocessing step in diagnosing ocular diseases. We present a computer-aided diagnostic system to automatically detect venous bead- ing of blood vessels. It comprises of two modules, referred to as the blood vessel extraction module (BVEM) and the venus beading detection module (VBDM). The former uses a bell-shaped Gaussian kernel with 12 azimuths to extract blood vessels while the latter applies a neural network-based shape cognitron to detect venous beading among the extracted blood vessels for diagnosis. Both modules are fully computer- automated. To evaluate the proposed system, 61 retinal images (32 beaded and 29 normal images) are used for performance evaluation. © 2000 Society of Photo-Optical Instrumentation Engineers. (S0091-3286(00)01305-2) Subject terms: bell-shaped Gaussian matched filter; blood vessel extraction mod- ule; detection; extraction; neural network; retinal images; shape cognitron; venus beading detection module.
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