Publications [#268842] of G. Allan Johnson

Papers Published

1. Song, J; Liu, Y; Gewalt, SL; Cofer, G; Johnson, GA; Liu, QH, Least-square NUFFT methods applied to 2-D and 3-D radially encoded MR image reconstruction., IEEE Trans Biomed Eng, vol. 56 no. 4 (April, 2009), pp. 1134-1142, ISSN 1558-2531 [19174334], [doi]
   (last updated on 2024/04/18)

   Abstract:
   Radially encoded MRI has gained increasing attention due to its motion insensitivity and reduced artifacts. However, because its samples are collected nonuniformly in the k-space, multidimensional (especially 3-D) radially sampled MRI image reconstruction is challenging. The objective of this paper is to develop a reconstruction technique in high dimensions with on-the-fly kernel calculation. It implements general multidimensional nonuniform fast Fourier transform (NUFFT) algorithms and incorporates them into a k-space image reconstruction framework. The method is then applied to reconstruct from the radially encoded k-space data, although the method is applicable to any non-Cartesian patterns. Performance comparisons are made against the conventional Kaiser-Bessel (KB) gridding method for 2-D and 3-D radially encoded computer-simulated phantoms and physically scanned phantoms. The results show that the NUFFT reconstruction method has better accuracy-efficiency tradeoff than the KB gridding method when the kernel weights are calculated on the fly. It is found that for a particular conventional kernel function, using its corresponding deapodization function as a scaling factor in the NUFFT framework has the potential to improve accuracy. In particular, when a cosine scaling factor is used, the NUFFT method is faster than KB gridding method since a closed-form solution is available and is less computationally expensive than the KB kernel (KB griding requires computation of Bessel functions). The NUFFT method has been successfully applied to 2-D and 3-D in vivo studies on small animals.

   Keywords:
   Animals • Computer Simulation • Image Processing, Computer-Assisted • Least-Squares Analysis* • Magnetic Resonance Imaging • Mice • Models, Statistical • Phantoms, Imaging • methods*