Image Reconstruction in K-space from MR Data Encoded with Ambiguous Gradient Fields

Overview

Journal Magn Reson Med

Publisher Wiley

Specialty Radiology

Date 2014 Apr 30

PMID 24777559

Citations 4

Authors

Gerrit Schultz

Daniel Gallichan

Hans Weber

Walter R T Witschey

Matthias Honal

Jurgen Hennig

Maxim Zaitsev

Affiliations

Soon will be listed here.

Abstract

Purpose: In this work, the limits of image reconstruction in k-space are explored when non-bijective gradient fields are used for spatial encoding.

Theory: The image space analogy between parallel imaging and imaging with non-bijective encoding fields is partially broken in k-space. As a consequence, it is hypothesized and proven that ambiguities can only be resolved partially in k-space, and not completely as is the case in image space.

Methods: Image-space and k-space based reconstruction algorithms for multi-channel radiofrequency data acquisitions are programmed and tested using numerical simulations as well as in vivo measurement data.

Results: The hypothesis is verified based on an analysis of reconstructed images. It is found that non-bijective gradient fields have the effect that densely sampled autocalibration data, used for k-space reconstruction, provide less information than a separate scan of the receiver coil sensitivity maps, used for image space reconstruction. Consequently, in k-space only the undersampling artifact can be unfolded, whereas in image space, it is also possible to resolve aliasing that is caused by the non-bijectivity of the gradient fields.

Conclusion: For standard imaging, reconstruction in image space and in k-space is nearly equivalent, whereas there is a fundamental difference with practical consequences for the selection of image reconstruction algorithms when non-bijective encoding fields are involved.

Citing Articles

Switching Circuit Optimization for Matrix Gradient Coils.

Kroboth S, Layton K, Jia F, Littin S, Yu H, Hennig J Tomography. 2019; 5(2):248-259.

PMID: 31245546 PMC: 6588200. DOI: 10.18383/j.tom.2018.00056.

Clinical Potential of a New Approach to MRI Acceleration.

Dispenza N, Littin S, Zaitsev M, Constable R, Galiana G Sci Rep. 2019; 9(1):1912.

PMID: 30760731 PMC: 6374397. DOI: 10.1038/s41598-018-36802-5.

Fast rotary nonlinear spatial acquisition (FRONSAC) imaging.

Wang H, Tam L, Constable R, Galiana G Magn Reson Med. 2015; 75(3):1154-65.

PMID: 25950279 PMC: 4637004. DOI: 10.1002/mrm.25703.

Image reconstruction in k-space from MR data encoded with ambiguous gradient fields.

Schultz G, Gallichan D, Weber H, Witschey W, Honal M, Hennig J Magn Reson Med. 2014; 73(2):857-64.

PMID: 24777559 PMC: 4617561. DOI: 10.1002/mrm.25152.

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