Width-wise vessel bifurcation for improved retinal vessel segmentation. (January 2022) - Khan, Tariq M.; Khan, Mohammad A.U.; Rehman, Naveed Ur; Naveed, Khuram; Afridi, Imran Uddin; Naqvi, Syed Saud; Raazak, Imran
Highlights: Small and large vessels are detected separately based on their unique characteristics. A directional triple-stick filtering are used to boost the detection of tiny vessels. BM3D filter is used to enhance specificity of the multi-scale line detection approach. Boundary compensation and morphological opening are used as key post processing steps. Abstract: Vessel local characteristics such as noise, illumination, and direction vary significantly in a fundus image, making it difficult to segment the vessel tree structure as a whole. To facilitate vessel detection, an alternative procedure proposed here, whereby retinal vessels first classified into two categories, large and small. Then, for its unique characteristics, each group has been processed with its own enhancement and detection filter. The sensitivity of the proposed method is boosted by capturing tiny vessels through a directional filter bank followed by its associated triple-stick filtering. Additionally, the specificity of the proposed method is enhanced through noise suppression attributed largely to the proposed BM3D filtering and multi-scale line detection approach. As a result, the detection accuracy on the DRIVE, STARE, and CHASE DB1 datasets is significantly improved, with scores of 0.9610, 0.9586, and 0.9578, respectively.