Medical images non-rigid registration based on Huber prior

Abstract

This study investigates a new non-rigid registration method based on Huber prior. The goal of image registration is to find a biologically plausible transformation which results in the spatial alignment of structurally or functionally corresponding regions in the two images. In order to improve the computing efficiency and registration precision, we used B-spline based free-form deformation (FFD) model. Our innovation is using Huber prior as penalty term of the energy function for better results. The FFD model with Huber prior which has high accuracy and strong robustness can settle the over-smoothing and edge information deficiency. We applied the proposed algorithm to both simulated data and real data registrations. Distinctly, the experiment results show that our method gets better results compared to conventional FFD registration algorithms.

Keywords:

• Medical images registration
• Multi-resolution
• Free-form deformation
• Huber prior

Acknowledgements

This work is partially supported by the National Science Foundation of China (Project No. 31000450), the Program of Pearl River Young Talents of Science and Technology in Guangzhou (No. 2012J2200041, 2013J2200065), Basic Research Program of Shenzhen City (No. JC201105170646A) and Major State Basic Research Development Program of China (973 Program, No. 2012CB732500).