Improving the Speed of MRI with Artificial Intelligence
Johnson PM, Recht MP, Knoll F (2020)
Publication Type: Journal article
Publication year: 2020
Journal
Book Volume: 24
Pages Range: 12-20
Article Number: 1900031
Journal Issue: 1
Abstract
Magnetic resonance imaging (MRI) is a leading image modality for the assessment of musculoskeletal (MSK) injuries and disorders. A significant drawback, however, is the lengthy data acquisition. This issue has motivated the development of methods to improve the speed of MRI. The field of artificial intelligence (AI) for accelerated MRI, although in its infancy, has seen tremendous progress over the past 3 years. Promising approaches include deep learning methods for reconstructing undersampled MRI data and generating high-resolution from low-resolution data. Preliminary studies show the promise of the variational network, a state-of-the-art technique, to generalize to many different anatomical regions and achieve comparable diagnostic accuracy as conventional methods. This article discusses the state-of-the-art methods, considerations for clinical applicability, followed by future perspectives for the field.
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APA:
Johnson, P.M., Recht, M.P., & Knoll, F. (2020). Improving the Speed of MRI with Artificial Intelligence. Seminars in Musculoskeletal Radiology, 24(1), 12-20. https://dx.doi.org/10.1055/s-0039-3400265
MLA:
Johnson, Patricia M., Michael P. Recht, and Florian Knoll. "Improving the Speed of MRI with Artificial Intelligence." Seminars in Musculoskeletal Radiology 24.1 (2020): 12-20.
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