Feature Based Nonrigid Brain MR Image Registration With Symmetric Alpha Stable Filters

—A new feature based nonrigid image registration method for magnetic resonance (MR) brain images is presented in this paper. Each image voxel is represented by a rotation invariant feature vector, which is computed by passing the input image volumes through a new bank of symmetric alpha stable ( ) filters. There are three main contributions presented in this paper. First, this work is motivated by the fact that the frequency spectrums of the brain MR images often exhibit non-Gaussian heavy-tail behavior which cannot be satisfactorily modeled by the conventional Gabor filters. To this end, we propose the use of filters to model such behavior and show that the Gabor filter is a special case of the filter. Second, the maximum response orientation (MRO) selection criterion is designed to extract rotation invariant features for registration tasks. The MRO selection criterion also significantly reduces the number of dimensions of feature vectors and therefore lowers the computation t...

• Type: Journal
• Year: 2010
• Where: TMI
• Authors: Shu Liao, Albert C. S. Chung
• Keywords: Feature Vectors, Images, TMI 2010, Voxel