A multi-scale non-linear vessel enhancement technique

We present an enhancement method based on nonlinear diffusion filter and statistical intensity approaches for smoothing and extracting 3-D vascular system from Magnetic Resonance Angiography (MRA) data. Our method distinguishes and enhances the vessels from the other embedded tissues. The Expectation Maximization (EM) technique is employed with non-linear diffusion in order to find the optimal contrast for enhancing vessels; therefore, smoothing while dimming the embedded tissues around the vessels and brightening the vessels. The non-linear diffusion filter smooths the homogeneous regions while preserving edges. The EM technique finds the optimal statistical parameters based on the probability distribution of the classes to discriminate the tissues in the image. Our enhancement technique has been applied to 4 3-D MRA-TOF datasets consisting of around 300 images and has been compared to the regularized Perona and Malik filter. Our experimental results show that the proposed method enhances the image, keeping only the vessels while eliminating the signal from other tissues. In comparison, the conventional non-linear diffusion filter keeps unwanted tissues in addition to the vessels.