Removal of Spurious Branches in Venous Networks

Following vein skeletonization, we can perform additional processing stages to enhance image quality. One key processing approach involves classifying each pixel as either a bifurcation point or node, followed by appropriate algorithmic actions. For bifurcation points detected through neighborhood analysis (typically using 8-connectivity pattern matching), we can implement branch splitting algorithms that separate the venous structure into two distinct vessels, better representing anatomical morphology. For node identification (endpoints or junction points), retention or removal decisions can be implemented based on application-specific parameters through conditional filtering. Furthermore, we employ spurious branch removal techniques that analyze branch length-to-width ratios and connectivity patterns to eliminate artifacts. These processing stages, implementable through morphological operations and graph-based traversal algorithms, provide clearer vascular structure visualization and improved morphological understanding, ultimately delivering higher-quality image data for medical diagnostics and related fields.