A Two-Level Cascade Classification Algorithm for Real-Time Bifurcation Detection in CTA Images of Blood Vessels

Abstract

We introduce a cascade classification algorithm for bifurcation detection in Computed Tomography Angiography (CTA) scans of blood vessels. The proposed algorithm analyzes the vessel surrounding by a trained classifier first, followed by an accurate segmentation of the vessel outer wall by Morphological Active Contour Without Edges and finally extracts the boundary features of the segmented object and classifies its shape by Approximate K-nearest Neighbour classifier. The algorithm shows encouraging and competitive results for blood vessels from various parts of a human body including head, neck and legs.