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Title
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Automatic high-bandwidth calibration and reconstruction of arbitrarily sampled parallel MRI
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Author
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Abstract
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| Today, many MRI reconstruction techniques exist for undersampled MRI data. Regularization-based techniques inspired by compressed sensing allow for the reconstruction of undersampled data that would lead to an ill-posed reconstruction problem. Parallel imaging enables the reconstruction of MRI images from undersampled multi-coil data that leads to a well-posed reconstruction problem. Autocalibrating pMRI techniques encompass pMRI techniques where no explicit knowledge of the coil sensivities is required. A first purpose of this paper is to derive a novel autocalibration approach for pMRI that allows for the estimation and use of smooth, but high-bandwidth coil profiles instead of a compactly supported kernel. These high-bandwidth models adhere more accurately to the physics of an antenna system. The second purpose of this paper is to demonstrate the feasibility of a parameter-free reconstruction algorithm that combines autocalibrating pMRI and compressed sensing. Therefore, we present several techniques for automatic parameter estimation in MRI reconstruction. Experiments show that a higher reconstruction accuracy can be had using high-bandwidth coil models and that the automatic parameter choices yield an acceptable result. |
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Language
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English
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Source (journal)
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PLoS ONE
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Publication
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2014
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ISSN
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1932-6203
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DOI
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10.1371/JOURNAL.PONE.0098937
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Volume/pages
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9
:6
(2014)
, 16 p.
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Article Reference
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e98937
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ISI
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000340947700044
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Medium
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E-only publicatie
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Full text (Publisher's DOI)
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Full text (open access)
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