Fast and accurate modeling of transient‐state, gradient‐spoiled sequences by recurrent neural networks-Reference-Cited by-同舟云学术

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Fast and accurate modeling of transient‐state, gradient‐spoiled sequences by recurrent neural networks

Published:2021-05-05 Issue: Volume: Page:
ISSN:0952-3480
Container-title:NMR in Biomedicine
language:en
Short-container-title:NMR in Biomedicine

Author:

Liu Hongyan¹^ORCID,Heide Oscar¹,Berg Cornelis A. T.¹,Sbrizzi Alessandro¹

Affiliation:

1. Center for Image Sciences University Medical Center Utrecht Utrecht the Netherlands

Funder

China Scholarship Council

Publisher

Wiley

Subject

Spectroscopy,Radiology Nuclear Medicine and imaging,Molecular Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/nbm.4527

Reference54 articles.

1. Disentangling molecular alterations from water‐content changes in the aging human brain using quantitative MRI;Filo S;Nat Commun.,2019

2. Quantitative brain relaxation atlases for personalized detection and characterization of brain pathology;Piredda GF;Magn Reson Med.,2020

3. Magnetic resonance fingerprinting;Ma D;Nature.,2013

4. Fast quantitative MRI as a nonlinear tomography problem;Sbrizzi A;Magn Reson Imaging.,2018

5. Extended phase graphs: dephasing, RF pulses, and echoes‐pure and simple;Weigel M;J Magn Reson Imaging.,2015

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2. Physics-Based Decoding Improves Magnetic Resonance Fingerprinting;Lecture Notes in Computer Science;2023

3. Efficient performance analysis and optimization of transient‐state sequences for multiparametric magnetic resonance imaging;NMR in Biomedicine;2022-11-23

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