Robust statistical registration of 3D ultrasound images using texture information

We investigate a new registration method for ultrasound volumes relying on on a statistical texture-basedsimilarity measure. Texture information is given by spatial Gabor filters and represented by statistical kernel-based distributions. The registration similarity measure is then defined as a probabilistic distance, derived from Bhattacharyya coefficient, between two statistical distributions. Given this similarity measure, parametric ultrasound image registration is stated as a robust minimization issue. We also exploit frequency properties of spatial Gabor filters to propose a multiresolution approach to perform this minimization. We provide a preliminary evaluation of the new registration technique on clinical data.

• Type: Conference
• Year: 2003
• Where: ICIP
• Authors: R. Francois, Ronan Fablet, Christian Barillot
• Keywords: ICIP 2003, Image Processing, Registration Similarity Measure, Spatial Gabor Filters, Statistical Kernel-based Distributions, Statistical Texture-basedsimilarity Measure, Ultrasound Image Registration