Contrast independent detection of branching points in network-like structures

Abstract

Many biomedical applications require the detection of branching structures in images. While several algorithms have been proposed for (semi-)automatic extraction of these structures, branching points usually need specific treatment. We propose a vector field-based approach to identify branching points in images. A vector field is calculated using a novel contrast-independent tensor representation based on local phase. Non-curvilinear structures, including junctions and end points, are detected using directional statistics of the principal orientation as defined by the tensor. Results on synthetic and real biomedical images show the robustness of the algorithm against changes in contrast, and its ability to detect junctions in highly complex images.