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Magnetic resonance imaging data is conventionally reconstructed using two dimensional discrete Fourier transforms. However, there is growing interest in other types of spectral estimation which minimize noise and artifacts due to truncated data. This note presents preliminary results--showing the improvement obtainable using a modified autoregressive model,(More)
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(More)
This paper discusses the two-dimensional implementation of a number of modified fast Fourier transform (FFT) algorithms that efficiently interpolate (zoom) magnetic resonance (MR) images. If the original image was sampled at a rate satisfying the Nyquist criterion, these algorithms would effectively increase the sampling rate, permitting image details to be(More)
The modeling of data is an alternative to conventional use of the fast Fourier transform (FFT) algorithm in the reconstruction of magnetic resonance (MR) images. The application of the FFT leads to artifacts and resolution loss in the image associated with the effective window on the experimentally-truncated phase encoded MR data. The transient error(More)
The resolution of magnetic resonance images reconstructed using the discrete Fourier transform (DFT) algorithm is limited by the effective window generated by the finite data length. The transient error reconstruction approach (TERA) is an alternative reconstruction method based on autoregressive moving average (ARMA) modeling techniques. Quantitative(More)
Manipulation of the data describing two-dimensional magnetic resonance (MR) images can be used to zoom an image, decrease image noise and artifacts by modeling, or emphasize object edges in the field of view. In this paper, a two-dimensional band-selectable digital filtering (2D-BSDF) technique is detailed. This can be used to decrease the computational(More)
In magnetic resonance (MR) imaging, excellent reconstructions are obtained on large data sets using the inverse discrete Fourier transform (IDFT). Modeling procedures have been proposed to overcome the image artifacts from the truncation of small data sets. In this paper, a relationship between image reconstruction using modeling and the standard IDFT is(More)
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