Low-rank iterative infilling for zero echo-time (ZTE) imaging.

PURPOSE: A new referenceless low-rank reconstruction technique has been introduced to address the issue of missing samples within the Zero Echo Time (ZTE) dead-time gap. METHODS: The proposed method reformulates the in-filling of the missing samples as an inverse problem subject to low-rank constraints. Its performance and robustness are evaluated through a comparative analysis that combines Monte Carlo computational simulations and data obtained from in vivo experiments. RESULTS: The proposed method is tested for dead-time gaps ranging up to 4.5 Nyquist dwells, across signal-to-noise ratio levels of 5, 10, 15, and 20 dB. Consistently superior performance is observed across all cases compared to algebraic and parallel imaging methods. The speed for convergence decreases exponentially as the dead-time gap expands. CONCLUSION: The proposed method enables artifact-free reconstruction up to dead-time gap of 4 Nyquist dwells and thereby supports ZTE imaging up to an imaging bandwidth of ± 41 . 67 $$ \pm 41.67 $$ kHz (assuming transmit and receive switching less than 30 μ $$ \mu $$ s). It demonstrates superior performance compared to algebraic and parallel imaging methods.

Publication Details

Journal
Apollo (University of Cambridge)
Published
2024-10-09
DOI
https://doi.org/10.17863/cam.112658
Primary Topic
Advanced MRI Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Low-rank iterative infilling for zero echo-time (ZTE) imaging.

Apollo (University of Cambridge)
Advanced MRI Techniques and Applications
article

Low-rank iterative infilling for zero echo-time (ZTE) imaging.

article en

Abstract

PURPOSE: A new referenceless low-rank reconstruction technique has been introduced to address the issue of missing samples within the Zero Echo Time (ZTE) dead-time gap. METHODS: The proposed method reformulates the in-filling of the missing samples as an inverse problem subject to low-rank constraints. Its performance and robustness are evaluated through a comparative analysis that combines Monte Carlo computational simulations and data obtained from in vivo experiments. RESULTS: The proposed method is tested for dead-time gaps ranging up to 4.5 Nyquist dwells, across signal-to-noise ratio levels of 5, 10, 15, and 20 dB. Consistently superior performance is observed across all cases compared to algebraic and parallel imaging methods. The speed for convergence decreases exponentially as the dead-time gap expands. CONCLUSION: The proposed method enables artifact-free reconstruction up to dead-time gap of 4 Nyquist dwells and thereby supports ZTE imaging up to an imaging bandwidth of ± 41 . 67 $$ \pm 41.67 $$ kHz (assuming transmit and receive switching less than 30 μ $$ \mu $$ s). It demonstrates superior performance compared to algebraic and parallel imaging methods.

Apollo (University of Cambridge)
National Institute for Health and Care Research, Department of Health and Social Care, NIHR Cambridge Biomedical Research Centre
Openalex Percentile: Top 54%
Advanced MRI Techniques and Applications
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Low-rank iterative infilling for zero echo-time (ZTE) imaging. · Apollo (University of Cambridge) (2024) | TGRS Research Map | TGRS