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Generalized self-calibrating simultaneous multi-slice MR image reconstruction from 3D Fourier encoding perspective
This work introduces a novel, k-space based one-step solution for simultaneous multi-slice MR image reconstruction from 3D Fourier encoding perspective. With undersampled SMS imaging, image reconstruction suffers from both inter-slice leakages and in-plane aliasing artifacts. Aliasing separation bec...
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Published in: | Medical image analysis 2022-11, Vol.82, p.102621-102621, Article 102621 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
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Summary: | This work introduces a novel, k-space based one-step solution for simultaneous multi-slice MR image reconstruction from 3D Fourier encoding perspective. With undersampled SMS imaging, image reconstruction suffers from both inter-slice leakages and in-plane aliasing artifacts. Aliasing separation becomes further challenging in the presence of discrepancies between calibration and imaging. To address them, in this work a measured SMS 3D k-space with additional calibrating signals is decomposed into SMS imaging and self-calibrating data sets. Extended controlled aliasing is performed by upsampling the measured data in the kz-direction. A slice-specific null space operator is then learned using extended self-calibration exploiting target slices and additional in-plane-shifted images. Inter-slice leakages and in-plane aliasing artifacts are jointly resolved in a single step by solving a constrained optimization problem in which null space reconstruction consistency is balanced with a Hankel-structured low rank prior while data fidelity in 3D Fourier space is enforced. Retrospective and prospective studies are performed to validate the effectiveness of the proposed method in various regions including knee and L-spine.
•Generalized self-calibrating SMS MR image reconstruction in 3D Fourier space.•Generalized mathematical forward signal model with incomplete SMS measurements.•Novel k-space based one-step SMS solution to jointly unfold artifacts in two directions.•Extended subspace learning strictly controlling signal passing and nulling among slices.•Suppressing inter-slice leakage artifacts even with short slice distance. |
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ISSN: | 1361-8415 1361-8423 |
DOI: | 10.1016/j.media.2022.102621 |