  In the medical domain, different computer-aided diagnosis systems have been
proposed to extract blood vessels from retinal fundus images for the clinical
treatment of vascular diseases. Accurate extraction of blood vessels from the
fundus images using a computer-generated method can help the clinician to
produce timely and accurate reports for the patient suffering from these
diseases. In this article, we integrate top-hat based preprocessing approach
with fine-tuned B-COSFIRE filter to achieve more accurate segregation of blood
vessel pixels from the background. The use of top-hat transformation in the
preprocessing stage enhances the efficacy of the algorithm to extract blood
vessels in presence of structures like fovea, exudates, haemorrhages, etc.
Furthermore, to reduce the false positives, small clusters of blood vessel
pixels are removed in the postprocessing stage. Further, we find that the
proposed algorithm is more efficient as compared to various modern algorithms
reported in the literature.
