Title: Joint MR image super-resolution reconstruction and sparse coefficients estimation

Authors: Di Zhang; Jiazhong He; Minghui Du

Addresses: School of Information Engineering, Guangdong Medical College, Dongguan, Guangdong, China ' Department of Physics, Shaoguan University, Shaoguan, Guangdong, China ' School of Electronics and Information, South China University of Technology, Guangzhou, Guangdong, China

Abstract: The spatial resolution of magnetic resonance (MR) image is determined by various instrumental limitations and physical considerations. This paper presents a new approach to MR image super-resolution reconstruction. Specifically, we incorporate nonlocal similarity, natural image prior, and sparsity prior into a unified, non-convex minimisation functional that contains both the unknown high-resolution image and the sparse coefficients. We also develop a majorisation-minimisation (MM) approach to solve the target non-convex functional. Experiments on MR image super-resolution reconstruction validate the efficiency of the proposed method.

Keywords: magnetic resonance imaging; MRI; super-resolution; sparse representation; natural image prior; nonlocal similarity; sparsity prior; image reconstruction; sparse coefficients; spatial resolution.

DOI: 10.1504/IJBET.2015.073427

International Journal of Biomedical Engineering and Technology, 2015 Vol.19 No.4, pp.373 - 392

Received: 29 Dec 2014
Accepted: 29 Jun 2015
Published online: 02 Dec 2015 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article