Application of Top-hat Transformation for Enhanced Blood Vessel Extraction
This work addresses the need for accurate computer-aided diagnosis of vascular diseases in medical imaging, though it appears incremental as it builds on existing methods.
The paper tackles the problem of extracting blood vessels from retinal fundus images by integrating a top-hat transformation preprocessing approach with a fine-tuned B-COSFIRE filter, achieving more accurate segregation of blood vessel pixels from the background and reducing false positives through postprocessing.
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.