NOVIFAST: A Fast Algorithm for Accurate and Precise VFA MRI Mapping

Gabriel Ramos-Llorden, Gonzalo Vegas-Sanchez-Ferrero, Marcus Bjork, Floris Vanhevel, Paul M Parizel, Raul San Jose Estepar, Arnold J den Dekker, Jan Sijbers

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)


In quantitative magnetic resonance mapping, the variable flip angle (VFA) steady state spoiled gradient recalled echo (SPGR) imaging technique is popular as it provides a series of high resolution weighted images in a clinically feasible time. Fast, linear methods that estimate maps from these weighted images have been proposed, such as DESPOT1 and iterative re-weighted linear least squares. More accurate, non-linear least squares (NLLS) estimators are in play, but these are generally much slower and require careful initialization. In this paper, we present NOVIFAST, a novel NLLS-based algorithm specifically tailored to VFA SPGR mapping. By exploiting the particular structure of the SPGR model, a computationally efficient, yet accurate and precise map estimator is derived. Simulation and in vivo human brain experiments demonstrate a twenty-fold speed gain of NOVIFAST compared with conventional gradient-based NLLS estimators while maintaining a high precision and accuracy. Moreover, NOVIFAST is eight times faster than the efficient implementations of the variable projection (VARPRO) method. Furthermore, NOVIFAST is shown to be robust against initialization.

Original languageEnglish
Article number8371285
Pages (from-to)2414-2427
Number of pages14
JournalIEEE Transactions on Medical Imaging
Issue number11
Publication statusPublished - Nov 2018
Externally publishedYes


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