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Abstract #1786

Optimizing Fusion Bootstrap Moves Solver (FBMS) regularization for improved B1+ mapping using Multi Spin-Echo brain sequences

Andreia C. Freitas1, Inês Sousa1, Andreia S. Gaspar1, Rui P.A.G. Teixeira2, Joseph V. Hajnal2, and Rita G. Nunes1,2
1ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Técnico – Universidade de Lisboa, Lisbon, Portugal, 2Centre for the Developing Brain, King's College London, London, United Kingdom

T2 mapping provides valuable tissue-specific MR information. To enable shorter scan times, multi spin-echo (MSE) sequences are commonly used but the achieved T2 accuracy using conventional mono-exponential fitting is poor. Improvements are possible by matching the measured signal to a pre-computed dictionary. Although simultaneous B1+ estimation is feasible, previous work demonstrated a bimodal behaviour. We investigate further improvements in B1+ accuracy using an iterative pixel-neighborhood based method (the Fusion Bootstrap Moves Solver), comparing different levels of spatial regularization. Improved B1+ accuracy and recovery of spatially smooth maps was demonstrated both in simulated and in-vivo brain data.

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