Compressed sensing for chemical shift‐based water–fat separation |
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| Authors: | Mariya Doneva Peter Börnert Holger Eggers Alfred Mertins John Pauly Michael Lustig |
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| Institution: | 1. Institute for Signal Processing, University of Lübeck, Lübeck, Germany;2. Tomographic Imaging Department, Philips Research Europe ‐ Hamburg, Hamburg, Germany;3. Department of Electrical Engineering, Magnetic Resonance Systems Research Laboratory, Stanford University, Stanford, California, USA;4. Department of Electrical Engineering and Computer Sciences, UC Berkeley, Berkeley, California, USA |
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| Abstract: | Multi echo chemical shift‐based water–fat separation methods allow for uniform fat suppression in the presence of main field inhomogeneities. However, these methods require additional scan time for chemical shift encoding. This work presents a method for water–fat separation from undersampled data (CS‐WF), which combines compressed sensing and chemical shift‐based water–fat separation. Undersampling was applied in the k‐space and in the chemical shift encoding dimension to reduce the total scanning time. The method can reconstruct high quality water and fat images in 2D and 3D applications from undersampled data. As an extension, multipeak fat spectral models were incorporated into the CS‐WF reconstruction to improve the water–fat separation quality. In 3D MRI, reduction factors of above three can be achieved, thus fully compensating the additional time needed in three‐echo water–fat imaging. The method is demonstrated on knee and abdominal in vivo data. Magn Reson Med, 2010. © 2010 Wiley‐Liss, Inc. |
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| Keywords: | MR imaging compressed sensing water– fat separation 3D imaging |
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