2021
DOI: 10.1098/rsta.2020.0197
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Synergistic multi-contrast cardiac magnetic resonance image reconstruction

Abstract: Cardiac magnetic resonance imaging (CMR) is an important tool for the non-invasive diagnosis of a variety of cardiovascular diseases. Parametric mapping with multi-contrast CMR is able to quantify tissue alterations in myocardial disease and promises to improve patient care. However, magnetic resonance imaging is an inherently slow imaging modality, resulting in long acquisition times for parametric mapping which acquires a series of cardiac images with different contrasts for signal fitting or dictionary matc… Show more

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Cited by 5 publications
(12 citation statements)
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References 101 publications
(166 reference statements)
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“…Similar sentiments have been expressed in the case of microscopy [18], fluorescence microscopy [19], PET (Position Emission Tomography) [20] and computed tomography [21,22]. See also [23][24][25][26][27][28] for further discussion and related issues. See also [14] for some theoretical analysis of instabilities and hallucinations in deep learning.…”
Section: Issues With Deep Learning For Inverse Problemsmentioning
confidence: 67%
See 1 more Smart Citation
“…Similar sentiments have been expressed in the case of microscopy [18], fluorescence microscopy [19], PET (Position Emission Tomography) [20] and computed tomography [21,22]. See also [23][24][25][26][27][28] for further discussion and related issues. See also [14] for some theoretical analysis of instabilities and hallucinations in deep learning.…”
Section: Issues With Deep Learning For Inverse Problemsmentioning
confidence: 67%
“…MNN acknowledges support from an NSERC CGS-M scholarship. Both authors would like to thank Vegard Antun and Matthew Colbrook for Springer Nature 2021 L A T E X template 26 Stable, accurate and efficient deep neural networks for inverse problems helpful advice and feedback. On behalf of all authors, the corresponding author states that there is no conflict of interest.…”
mentioning
confidence: 99%
“…Many newer techniques utilize alternative sampling trajectories which frequently sample through the center of k-space, such as radial, rosette or spiral trajectories. These trajectories are desirable because they allow detection and extraction of respiratory and cardiac motion, thus enabling newer techniques to be free-breathing or self-gated ( 35 ). This reduces scanning complexity for the technologist, as no ECG electrodes or respiratory navigators are required.…”
Section: Basics Of Multi-parametric Sparse Sampling Methodsmentioning
confidence: 99%
“…To address these limitations, several working groups have focused on the development of fast and user-friendly acquisition methods ( 11 34 ). One proposed approach is the use of “one-click” scans, where multiple cardiac parameters (such as T1 relaxation, T2 relaxation, or cardiac motion) are collected simultaneously with less prospective planning ( 22 , 23 , 35 , 36 ). These techniques have been collectively called Simultaneous Multiparametric Acquisition and Reconstruction Techniques (SMART) ( 37 ).…”
Section: Introductionmentioning
confidence: 99%
“…One of the challenges is long reconstruction times. Deep learning-based parameter mapping is a promising alternative which ensures accurate parameter estimation in a clinically feasible time-frame [ 2 ].…”
Section: Contributions In This Issuementioning
confidence: 99%