Magnetic Resonance Fingerprinting

Overview

Journal Nature

Specialty Science

Date 2013 Mar 15

PMID 23486058

Citations 572

Authors

Dan Ma

Vikas Gulani

Nicole Seiberlich

Kecheng Liu

Jeffrey L Sunshine

Jeffrey L Duerk

Mark A Griswold

Affiliations

Soon will be listed here.

Abstract

Magnetic resonance is an exceptionally powerful and versatile measurement technique. The basic structure of a magnetic resonance experiment has remained largely unchanged for almost 50 years, being mainly restricted to the qualitative probing of only a limited set of the properties that can in principle be accessed by this technique. Here we introduce an approach to data acquisition, post-processing and visualization--which we term 'magnetic resonance fingerprinting' (MRF)--that permits the simultaneous non-invasive quantification of multiple important properties of a material or tissue. MRF thus provides an alternative way to quantitatively detect and analyse complex changes that can represent physical alterations of a substance or early indicators of disease. MRF can also be used to identify the presence of a specific target material or tissue, which will increase the sensitivity, specificity and speed of a magnetic resonance study, and potentially lead to new diagnostic testing methodologies. When paired with an appropriate pattern-recognition algorithm, MRF inherently suppresses measurement errors and can thus improve measurement accuracy.

Citing Articles

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Flexible and cost-effective deep learning for accelerated multi-parametric relaxometry using phase-cycled bSSFP.

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Deep learning initialized compressed sensing (Deli-CS) in volumetric spatio-temporal subspace reconstruction.

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Incorporating Spatial and Spectral Saturation Modules Into MR Fingerprinting.

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