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Abstract #5649

Improved Accuracy of Accelerated 3D T2* Mapping with Coherent Parallel Maximum Likelihood Estimation

Wajiha Bano1,2, Mohammad Golbabee1, Arnold Julian Vinoj Benjamin1,2, Ian Marshall2, and Michael Davies1

1School of Engineering, Institute for Digital Communications, University of Edinburgh, Edinburgh, United Kingdom, 2Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom

We propose an approach that can reconstruct isotropic T2* Maps from undersampled data with improved accuracy by utilizing the phase information. Our approach extends the acceleration attained in Parallel Imaging(PI) to Maximum Likelihood Estimation (MLE) by imposing the exponential relaxation directly in the complex signal domain. The method was tested on a Multiecho Gradient Echo(MEGE) T2* mapping experiment in a numerical phantom and a human brain with realtime (prospective) undersampling. The approach showed that incorporating the phase information to perform coherent fitting resulted in better denoising and improved accuracy of the parametric maps.

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