Paper
5 March 2007 Continuous criterion for parallel MRI reconstruction using B-spline approximation (PROBER)
Jan Petr, Jan Kybic
Author Affiliations +
Abstract
Parallel MRI is a way to use multiple receiver coils with distinct spatial sensitivities to increase the speed of the MRI acquisition. The acquisition is speeded up by undersampling in the phase-encoding direction and the resulting data loss and aliasing is compensated for by the use of the additional information obtained from several receiver coils. The task is to reconstruct an unaliased image from a series of aliased images. We have proposed an algorithm called PROBER that takes advantage of the smoothness of the reconstruction transformation in space. B-spline functions are used to approximate the reconstruction transformation. Their coefficients are estimated at once minimizing the total expected reconstruction error. This makes the reconstruction less sensitive to noise in the reference images and areas without signal in the image. We show that this approach outperforms the SENSE and GRAPPA reconstruction methods for certain coil configurations. In this article, we propose another improvement, consisting of a continuous representation of the B-splines to evaluate the error instead of the discretely sampled version. This solves the undersampling issues in the discrete B-spline representation and offers higher reconstruction quality which has been confirmed by experiments. The method is compared with the discrete version of PROBER and with commercially used algorithms GRAPPA and SENSE in terms of artifact suppression and reconstruction SNR.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jan Petr and Jan Kybic "Continuous criterion for parallel MRI reconstruction using B-spline approximation (PROBER)", Proc. SPIE 6512, Medical Imaging 2007: Image Processing, 651241 (5 March 2007); https://doi.org/10.1117/12.708150
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KEYWORDS
Signal to noise ratio

Magnetic resonance imaging

Receivers

Reconstruction algorithms

Error analysis

In vivo imaging

Computer programming

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