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Abstract #3982

Automatic, Non-Regularized Nonlinear Dipole Inversion for Fast and Robust Quantitative Susceptibility Mapping

Carlos Milovic1 and Karin Shmueli1
1Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom

Quantitative Susceptibility Mapping (QSM) is an ill-posed inverse problem often solved by regularization: minimizing a functional until it converges. This is usually time-consuming, requiring fine-tuning of several parameters by many repetitions of the whole optimization solver. Nonlinear Dipole Inversion is a QSM method that solves a nonlinear Tikhonov-regularized functional with a gradient descent solver. We show that stopping this method early provides optimal results, largely independent of the regularization weight. Here, we propose a non-regularized nonlinear conjugate gradient solver with a new stopping criterion based on analysing susceptibility map spatial frequency coefficients to achieve fast, parameter-free and automatic QSM.

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