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Quantitative evaluation of several partial fourier reconstruction algorithms used in mri
Author(s) -
McGibney G.,
Smith M. R.,
Nichols S. T.,
Crawley A.
Publication year - 1993
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.1910300109
Subject(s) - algorithm , fourier transform , convolution (computer science) , iterative reconstruction , frequency domain , computer science , redundancy (engineering) , fourier analysis , finite impulse response , reconstruction algorithm , mathematics , artificial intelligence , computer vision , mathematical analysis , artificial neural network , operating system
Partial Fourier reconstruction algorithms exploit the redundancy in magnetic resonance data sets so that half of the data is calculated during image reconstruction rather than acquired. The conjugate synthesis, Margosian, homodyne detection, Cuppen and POCS algorithms are evaluated using spatial frequency domain analysis to show their characteristics and where limitations may occur. The phase correction used in partial Fourier reconstruction is equivalent to a convolution in the frequency domain and the importance of accurately implementing this convolution is demonstrated. New reconstruction approaches, based on passing the partial data through a phase correcting, finite impulse response (FIR), digital filter are suggested. These FIR and MoFIR algorithms have a speed near that of the Margosian and homodyne detection reconstructions, but with a lower error; close to that of the Cuppen/POCS iterative approaches. Quantitative analysis of the partial Fourier algorithms, tested with three phase estimation techniques, are provided by comparing artificial and clinical data reconstructed using full and partial Fourier techniques.