Super resolution image reconstruction in parallel magnetic resonance imaging

In clinical applications, images with high resolution are often desired and required which may provide more details for doctors to make precise diagnosis. In this paper, an approach is proposed to increase image resolution of parallel magnetic resonance imaging. Since different receiver coils have different sensitivity profiles, different receiver channel models are constructed to map the original image information to low resolution images of different channels. Based on these models, the degradation function of every low resolution image can be obtained to compute the high resolution image iteratively using the well known super resolution approach. An in-vivo experiment is also provided to illustrate the feasibility and robustness of the proposed approach.

[1]  Hayit Greenspan,et al.  MRI inter-slice reconstruction using super-resolution , 2002 .

[2]  Hayit Greenspan,et al.  Super-Resolution in Medical Imaging , 2009, Comput. J..

[3]  P. Boesiger,et al.  SENSE: Sensitivity encoding for fast MRI , 1999, Magnetic resonance in medicine.

[4]  Pierre Kornprobst,et al.  Superresolution in MRI and its influence in statistical analysis , 2002 .

[5]  Rachid Deriche,et al.  A Superresolution Framework for fMRI Sequences and Its Impact on Resulting Activation Maps , 2003, MICCAI.

[6]  Rachid Deriche,et al.  Half-quadratic regularization for MRI image restoration , 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..

[7]  A. Murat Tekalp,et al.  POCS-based restoration of space-varying blurred images , 1994, IEEE Trans. Image Process..

[8]  John W. Clark,et al.  Comparison between two super-resolution implementations in PET imaging. , 2009, Medical physics.

[9]  P. P. Vaidyanathan,et al.  Cyclic LTI systems in digital signal processing , 1999, IEEE Trans. Signal Process..

[10]  C Bodensteiner,et al.  Achieving super‐resolution X‐ray imaging with mobile C‐arm devices , 2009, The international journal of medical robotics + computer assisted surgery : MRCAS.

[11]  Rachid Deriche,et al.  The use of super‐resolution techniques to reduce slice thickness in functional MRI , 2004, Int. J. Imaging Syst. Technol..

[12]  Andre Souza,et al.  Model-based super-resolution for MRI , 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.