Methods for the detection of blood vessels in retinal fundus images and reduction of false-positive pixels around the optic nerve head

Detection of blood vessels in retinal fundus images is an important initial step in the development of systems for computer-aided diagnosis of pathologies of the eye. In this study, we perform multifeature analysis for the detection of blood vessels in retinal fundus images. The techniques implemented include multiscale vesselness measures and Gabor filters. The selection of an appropriate threshold is crucial for accurate detection of retinal blood vessels. We propose an adaptive threshold selection method for this purpose. We also propose a postprocessing technique for removal of false-positive pixels around the optic nerve head. Values of the area under the receiver operating characteristic curve of up to 0.9616 were obtained using the 20 test images of the DRIVE database.