Accelerated dynamic MRI using patch regularization for implicit motion compensation. Issue 3 (19th April 2016) - Mohsin, Yasir Q.; Lingala, Sajan Goud; DiBella, Edward; Jacob, Mathews
Abstract : 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