N-sift: N-dimensional scale invariant feature transform for matching medical images

We present a fully automated multimodal medical image match-ing technique. Our method extends the concepts used in the computer vision SIFT technique for extracting and match-ing distinctive scale invariant features in 2D scalar images to scalar images of arbitrary dimensionality. This extension involves using hyperspherical coordinates for gradients and multidimensional histograms to create the feature vectors. These features were successfully applied to determine accurate fea-ture point correspondence between pairs of medical images (3D) and dynamic volumetric data (3D+time). Index terms—Biomedical image processing, Image match-ing, Feature extraction 1