An extraction method of cerebral vessels based on multi-threshold otsu classification and hessian matrix enhancement filtering

Abstract

An integrated cerebral vascular enhancement method based on the multi-threshold Otsu classification for gray voxels relative to cerebral vessels and the multi-scale Hessian feature for the tubular object enhancement is presented. It implements the multi-threshold Otsu classification to get the cerebral vascular gray voxels, and exploits these voxels' geometric characteristics by Hessian matrix. And Hessian matrix's eigenvalues and eigenvectors are used to form a tubular object response function which would be used for further mathematical morphology processing to smooth and mend vessels' region. Compared with other tubular object enhancement methods, it behaves higher accurateness with stable robustness. © Springer Science+Business Media Dordrecht 2014.