Journal article
Mean square optimal NUFFT approximation for efficient non-Cartesian MRI reconstruction
Journal of magnetic resonance (1997), Vol.242, pp.126-135
05/2014
DOI: 10.1016/j.jmr.2014.01.016
PMCID: PMC4008684
PMID: 24637054
Abstract
[Display omitted]\n•Novel NUFFT approximations for iterative non-Cartesian MRI reconstruction.•Better reconstructed image quality with less approximation error.•Considerably less memory demand compared to current algorithms, enabling implementations on GPUs.\nThe fast evaluation of the discrete Fourier transform of an image at non-uniform sampling locations is key to efficient iterative non-Cartesian MRI reconstruction algorithms. Current non-uniform fast Fourier transform (NUFFT) approximations rely on the interpolation of oversampled uniform Fourier samples. The main challenge is high memory demand due to oversampling, especially when multidimensional datasets are involved. The main focus of this work is to design an NUFFT algorithm with minimal memory demands. Specifically, we introduce an analytical expression for the expected mean square error in the NUFFT approximation based on our earlier work. We then introduce an iterative algorithm to design the interpolator and scale factors. Experimental comparisons show that the proposed optimized NUFFT scheme provides considerably lower approximation errors than the previous designs [1] that rely on worst case error metrics. The improved approximations are also seen to considerably reduce the errors and artifacts in non-Cartesian MRI reconstruction.
Details
- Title: Subtitle
- Mean square optimal NUFFT approximation for efficient non-Cartesian MRI reconstruction
- Creators
- Zhili Yang - University of Rochester, 659 W Randolph Street, Apt 717, Chicago, IL 60661, United StatesMathews Jacob - University of Iowa, 3314 Seamans Center for the Engineering Arts and Sciences, Iowa City, IA 52240, United States
- Resource Type
- Journal article
- Publication Details
- Journal of magnetic resonance (1997), Vol.242, pp.126-135
- DOI
- 10.1016/j.jmr.2014.01.016
- PMID
- 24637054
- PMCID
- PMC4008684
- NLM abbreviation
- J Magn Reson
- ISSN
- 1090-7807
- eISSN
- 1096-0856
- Publisher
- Elsevier BV
- Language
- English
- Date published
- 05/2014
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology; Electrical and Computer Engineering; Iowa Neuroscience Institute; Radiation Oncology
- Record Identifier
- 9984070994202771
Metrics
24 Record Views