Cerebral vascular enhancement using a weighted 3D symmetry filter

The automated detection of cerebral vessels is of great importance in understanding of the diagnosis, treatment and mechanism of many brain vascular pathologies. However, automatic vessel detection from 3D angiography continues to be an open issue. In this paper we introduce a novel 3D symmetry filter that has excellent performance on enhancing vessels in magnetic resonance angiography (MRA). The proposed filter not only takes into account of local phase features estimated by using a quadrature filter so as to distinguish between lines and the edges, but also uses the weighted geometric mean of the blurred and shifted responses of the quadrature filter, which allows more tolerance in the position of the respective contours. As a result this filter can produce a strong response to the vascular features despite variations in scale, contrast, and bifurcations in images. Our results demonstrate its superior performance to other state-of-the-art methods.