Super-resolution reconstruction of MR image sequences with contrast modeling

Authors:
Justin P. Haldar;Diego Hernando;Zhi-Pei Liang
Affiliations:
Department of Electrical and Computer Engineering, Beckman Institute, University of Illinois at Urbana-Champaign;Department of Electrical and Computer Engineering, Beckman Institute, University of Illinois at Urbana-Champaign;Department of Electrical and Computer Engineering, Beckman Institute, University of Illinois at Urbana-Champaign
Venue:
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
Year:
2009

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Abstract

Quantitative MR imaging experiments (e.g., to measure relaxation and diffusion properties of tissues) often require image sequences with different contrast in each frame. However, high-resolution acquisition of each frame can lead to prohibitively long experiments. In this work, we investigate the possibility of utilizing a parametric contrast model to synthesize high-resolution information. Theoretical analysis and empirical evidence indicates that this kind of super-resolution can be possible, though robustness is dependent on a number of factors (e.g., the contrast model and the experiment design). In particular, it is found that conventional low-frequency sampling leads to significant information loss, but that alternative experiments can overcome this limitation. Experimental results are shown in the context of T2* relaxation mapping.