Keywords: Acquisition Methods, High-Field MRI
Motivation: The introduction of Machine Learning-based Image Reconstruction ("Deep Learning") offers a fresh opportunity to explore MR parameter space without the restrictive requirement to maximise MR signal.
Goal(s): Demonstrate an application of the Low Stochastic Regime approach using low flip angle refocusing with good SNR and strong tissue contrast.
Approach: Fast Spin Echo (FSE) images were acquired using reduced flip angle refocusing and extended echo train lengths, in combination with Deep Learning-Reconstruction (“DL-Recon”).
Results: Using DL-Recon to effectively weaken the conventional constraint of maximising MR signal, the redesigned sequence produced images with lower RF power deposition but similar contrast to the product CPMG sequence.
Impact: Clinical applications where T2-weighted imaging is SAR-limited.
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