3D multi-scale vessel enhancement filtering based on curvature measurements: application to time-of-flight MRA ?
In this paper we evaluate the use of voxel intensity curvature measurements to enhance vessels in 3D MRA images. We compare a multi-scale discrete kernel filter (MaxCurve) to the Hessian matrix based filter proposed by Frangi and co-workers. The MaxCurve filter is based on the maximum difference between the negative curvature computed along orthogonal lines defined by a 333 kernel. Filter performance is assessed using measures of vessel and background separation (contrast and the area under the ROC curve). Filter parameters are optimized using a training set of four typical time-of-flight MRA images and tested on a separate set of ten MRA images with the same acquisition parameters. The filters tended to provide good MIP image contrast enhancement. The filters are applied to MRA images acquired with different parameters and field strengths indicating potential usefulness for a variety of images. Overall the discrete kernel and Hessian matrix filter performed quite similarly.
filtering magnetic resonance angiography intra-cranial vessels