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Abstract #4999

A multi-scale approach to quantitative susceptibility mapping (MSDI)

Julio Acosta-Cabronero1, Carlos Milovic2,3, Cristian Tejos2, and Martina F Callaghan1

1Wellcome Centre for Human Neuroimaging, UCL Insitute of Neurology, University College London, London, United Kingdom, 2Department of Electrical Engineering, Pontificia Universidad Catolica de Chile, Santiago, Chile, 3Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, Chile

We propose a new QSM algorithm, namely multi-scale dipole inversion (MSDI), which builds on the nonlinear MEDI (nMEDI) framework incorporating two additional features: (i) improved error control through dynamic phase-reliability compensation across harmonic scales and (ii) scale-specific use of the morphological prior. MSDI is the first algorithm to rank in the top-10 for all performance metrics evaluated in the 2016 QSM Reconstruction Challenge. It also demonstrates lower variance than nMEDI in a reproducibility test.

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