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Accelerated dynamic MRI using patch regularization for implicit motion compensation
Author(s) -
Mohsin Yasir Q.,
Lingala Sajan Goud,
DiBella Edward,
Jacob Mathews
Publication year - 2017
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.26215
Subject(s) - regularization (linguistics) , computer science , motion estimation , motion compensation , algorithm , computer vision , artificial intelligence , metric (unit) , motion (physics) , smoothness , mathematics , operations management , economics , mathematical analysis
Purpose To introduce a fast algorithm for motion‐compensated accelerated dynamic MRI. Methods An efficient patch smoothness regularization scheme, which implicitly compensates for inter‐frame motion, is introduced to recover dynamic MRI data from highly undersampled measurements. The regularization prior is a sum of distances between each rectangular patch in the dataset with other patches in the dataset using a saturating distance metric. Unlike current motion estimation and motion compensation (ME‐MC) methods, the proposed scheme does not require reference frames or complex motion models. The proposed algorithm, which alternates between inter‐patch shrinkage step and conjugate gradient algorithm, is considerably more computationally efficient than ME‐MC methods. The reconstructions obtained using the proposed algorithm is compared against state‐of‐the‐art methods. Results The proposed method is observed to yield reconstructions with minimal spatiotemporal blurring and motion artifacts. In comparison to the existing state‐of‐the‐art ME‐MC methods, PRICE provides comparable or even better image quality with faster reconstruction times (approximately nine times faster). Conclusion The presented scheme enables computationally efficient and effective motion‐compensated reconstruction in a variety of applications with large inter‐frame motion and contrast changes. This algorithm could be seen as an alternative over the current state‐of‐the‐art ME‐MC schemes that are computationally expensive. Magn Reson Med 77:1238–1248, 2017. © 2016 International Society for Magnetic Resonance in Medicine