A modulated closed form solution for quantitative susceptibility mapping--a thorough evaluation and comparison to iterative methods based on edge prior knowledge
Autor: | Yves Wiaux, José P. Marques, Rolf Gruetter, Diana Khabipova |
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Rok vydání: | 2014 |
Předmět: |
Adult
Male Multiple Sclerosis Iterative method Cognitive Neuroscience Computation Imaging phantom Image Processing Computer-Assisted Humans Computer vision Computer Simulation Gray Matter Mathematics Ground truth Brain Mapping business.industry Phantoms Imaging Isotropy Quantitative susceptibility mapping Magnetic Resonance Imaging White Matter Knowledge Neurology Norm (mathematics) Female Artificial intelligence Closed-form expression business Artifacts Algorithm Algorithms |
Zdroj: | NeuroImage. 107 |
ISSN: | 1095-9572 |
Popis: | The aim of this study is to perform a thorough comparison of quantitative susceptibility mapping (QSM) techniques and their dependence on the assumptions made. The compared methodologies were: two iterative single orientation methodologies minimizing the l2, l1TV norm of the prior knowledge of the edges of the object, one over-determined multiple orientation method (COSMOS) and anewly proposed modulated closed-form solution (MCF). The performance of these methods was compared using a numerical phantom and in-vivo high resolution (0.65 mm isotropic) brain data acquired at 7 T using a new coil combination method. For all QSM methods, the relevant regularization and prior-knowledge parameters were systematically changed in order to evaluate the optimal reconstruction in the presence and absence of a ground truth. Additionally, the QSM contrast was compared to conventional gradient recalled echo (GRE) magnitude and R2* maps obtained from the same dataset. The QSM reconstruction results of the single orientation methods show comparable performance. The MCF method has the highest correlation (corrMCF = 0.95, r2MCF = 0.97) with the state of the art method (COSMOS) with additional advantage of extreme fast computation time. The l-curve method gave the visually most satisfactory balance between reduction of streaking artifacts and over-regularization with the latter being overemphasized when the using the COSMOS susceptibility maps as ground-truth. R2* and susceptibility maps, when calculated from the same datasets, although based on distinct features of the data, have a comparable ability to distinguish deep gray matter structures. |
Databáze: | OpenAIRE |
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