## Abstract Increased spatiotemporal resolution in MRI can be achieved by the use of parallel acquisition strategies, which simultaneously sample reduced __k__‐space data using the information from multiple receivers to reconstruct full‐FOV images. The price for the increased spatiotemporal resolut
Parallel image reconstruction using B-spline approximation (PROBER)
✍ Scribed by Jan Petr; Jan Kybic; Michael Bock; Sven Müller; Václav Hlaváč
- Publisher
- John Wiley and Sons
- Year
- 2007
- Tongue
- English
- Weight
- 645 KB
- Volume
- 58
- Category
- Article
- ISSN
- 0740-3194
No coin nor oath required. For personal study only.
✦ Synopsis
Abstract
A new reconstruction method for parallel MRI called PROBER is proposed. The method PROBER works in an image domain similar to methods based on Sensitivity Encoding (SENSE). However, unlike SENSE, which first estimates the spatial sensitivity maps, PROBER approximates the reconstruction coefficients directly by B‐splines. Also, B‐spline coefficients are estimated at once in order to minimize the reconstruction error instead of estimating the reconstruction in each pixel independently (as in SENSE). This makes the method robust to noise in reference images. No presmoothing of reference images is necessary. The number of estimated parameters is reduced, which speeds up the estimation process. PROBER was tested on simulated, phantom, and in vivo data. The results are compared with commercial implementations of the algorithms SENSE and GRAPPA (Generalized Autocalibrating Partially Parallel Acquisitions) in terms of elapsed time and reconstruction quality. The experiments showed that PROBER is faster than GRAPPA and SENSE for images wider than 150 × 150 pixels for comparable reconstruction quality. With more basis functions, PROBER outperforms both SENSE and GRAPPA in reconstruction quality at the cost of slightly increased computational time. Magn Reson Med 58:582–591, 2007. © 2007 Wiley‐Liss, Inc.
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