Oriented filters for vessel contrast enhancement with local directional evidence
Vascular structures occur in abundance within biomedical and biological image processing applications. From detecting retinal blood vessels to analyzing shape and connectivity of neurons, segmentation of vascular structures has received significant attention in the literature. Robust segmentation often demands a preprocessing stage involving enhancement of the tubular objects. We propose a novel method to enhance vascular structures from low contrast images by incorporating evidence of neighboring tubular structures in addition to the local vessel detection. We show that the proposed algorithm, called local directional evidence (LDE), is capable of handling bifurcations, intensity inhomogeneity and complex geometry of the vessels, thus providing a robust preprocessing for segmentation. Experiments on a collection of biological images containing vascular objects suggest efficacy of LDE when used as a precursor to segmentation. We observe that LDE improves the average segmentation performance by 63% on our database over the vessel enhancing filter of [1].