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Robust Retinal Vessel Segmentation using Vessel's Location Map and Frangi Enhancement Filter

Robust Retinal Vessel Segmentation using Vessel's Location Map and Frangi Enhancement Filter

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The analysis of retinal vascular is quite important because many diseases including stroke, diabetic retinopathy (DR) and coronary heart diseases can damage retinal vessel structure. In this research, a technique has been proposed using a combination of pre-processing steps, vessel enhancement techniques, segmentation and post-processing. The pre-processing section comprises of adaptive histogram equalisation for dissimilarity enhancement between vessels and background, a morphological top hat filter for macula and optic disc removal and high boost filtering, edges enhancement. Frangi filter is applied at multi-scale for enhancement of different vessel widths. Segmentation has been performed using global Otsu thresholding with some offset applied on difference image and enhanced image separately. A vessel location map (VLM) has been extracted using the post-processing steps of raster to vector transformed area and eccentricity-based threshold to eliminate the exudate/unwanted region from binarised image. Post-processing has been used in a new way to reject misclassified vessel pixels. The final segmented image has been obtained by using pixel-by-pixel AND operation between VLM and Frangi binarised image. The method has been rigorously analysed using STARE and DRIVE datasets.

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