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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Milles, J. Versluis, M.J. Webb, A.G. Reiber, J.H.C. |
| Copyright Year | 2010 |
| Description | Author affiliation: CJ Gorter center for high field MRI, Department of Radiology, Leiden University Medical Center, the Netherlands (Versluis, M.J.; Webb, A.G.) || Division of Image Processing, Department of Radiology, Leiden University Medical Center, the Netherlands (Milles, J.; Reiber, J.H.C.) |
| Abstract | Compressed Sensing is a recently developed technique that enables the reconstruction of sparsely sampled MR data, thus enabling much faster image acquisitions than using conventional approaches which are limited by the Nyquist criterion. Even though this method has been shown to provide visually acceptable results in a number of applications, no quantitative evaluation of the quality of the image data reconstructed using this method have yet been provided. In this paper we evaluate Compressed Sensing reconstruction in terms of sensitivity to its intrinsic reconstruction parameters as well as to the acquisition strategy both with simulated and experimental time-of-flight angiography data acquired on a 7T clinical MR scanner. Results show that Compressed Sensing reconstruction outperforms traditional methods of undersampling such as simple zero-filling and provides data with acceptable quality at undersampling rates up to a factor of ten. Such an acquisition framework therefore appears to be a valid and promising approach for reducing data acquisition time. |
| Starting Page | 1 |
| Ending Page | 4 |
| File Size | 533712 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424465590 |
| e-ISBN | 9781424465613 |
| DOI | 10.1109/ITAB.2010.5687775 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-11-03 |
| Publisher Place | Greece |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Image reconstruction Image segmentation Variable speed drives Data models Computational modeling Catheters Compressed sensing |
| Content Type | Text |
| Resource Type | Article |
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