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Model resolution-based deconvolution for improved quantitative susceptibility mapping

Mathew, RS and Paluru, N and Yalavarthy, PK (2023) Model resolution-based deconvolution for improved quantitative susceptibility mapping. In: NMR in Biomedicine .

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Official URL: https://doi.org/10.1002/nbm.5055


Quantitative susceptibility mapping (QSM) utilizes the relationship between the measured local field and the unknown susceptibility map to perform dipole deconvolution. The aim of this work is to introduce and systematically evaluate the model resolution-based deconvolution for improved estimation of the susceptibility map obtained using the thresholded k-space division (TKD). A two-step approach has been proposed, wherein the first step involves the TKD susceptibility map computation and the second step involves the correction of this susceptibility map using the model-resolution matrix. The TKD-estimated susceptibility map can be expressed as the weighted average of the true susceptibility map, where the weights are determined by the rows of the model-resolution matrix, and hence a deconvolution of the TKD susceptibility map using the model-resolution matrix yields a better approximation to the true susceptibility map. The model resolution-based deconvolution is realized using closed-form, iterative, and sparsity-regularized implementations. The proposed approach was compared with L2 regularization, TKD, rescaled TKD in superfast dipole inversion, the modulated closed-form method, and iterative dipole inversion, as well as sparsity-regularized dipole inversion. It was observed that the proposed approach showed a substantial reduction in the streaking artifacts across 94 test volumes considered in this study. The proposed approach also showed better error reduction and edge preservation compared with other approaches. The proposed model resolution-based deconvolution compensates for the truncation of zero coefficients in the dipole kernel at the magic angle and hence provides a closer approximation to the true susceptibility map compared with other direct methods. © 2023 John Wiley & Sons Ltd.

Item Type: Journal Article
Publication: NMR in Biomedicine
Publisher: John Wiley and Sons Ltd
Additional Information: The copyright for this article belongs to John Wiley and Sons Ltd
Keywords: Mapping; Matrix algebra, Deconvolutions; Dipole deconvolution; K-space; Model resolution; Model resolution matrixes; Reconstruction; Space division; Susceptibility mapping; Susceptibility maps; Truncation parameter, Iterative methods, article; artifact; deconvolution; dipole
Department/Centre: Division of Interdisciplinary Sciences > Computational and Data Sciences
Date Deposited: 18 Dec 2023 04:53
Last Modified: 18 Dec 2023 04:53
URI: https://eprints.iisc.ac.in/id/eprint/83506

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