Paper
10 March 2006 Theoretical framework for analyzing MR imaging of dynamic objects using filters and downsamplers
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Abstract
Reconstruction methods for MR imaging of dynamic objects have traditionally been analyzed using the projection slice theorem. In this paper, we present a new theoretical framework for analyzing MR imaging of dynamic objects. Our framework reinterprets the object stationarity assumption in the MR reconstruction techniques as a combination of filtering and downsampling operations performed on the acquired k-space data. We have analyzed our results in x-f (spatial coordinate - temporal frequency) space using a time-sequential analysis. While the projection slice theorem has only be used to analyze the Cartesian sampling pattern, the new framework can analyze any arbitrary sampling pattern with a given reconstruction algorithm. Further, the new theoretical framework can be used to analyze the effect of relaxing the object stationarity assumption over the reconstructed MR images. We have demonstrated the use of our framework by analyzing two popular image reconstruction techniques, namely view-sharing and UNFOLD. In the analysis of view-sharing, we have confirmed the fact that interleaved and bit reversed k-space sampling patterns provide better artifact suppression for dynamic MR imaging. We propose using a different filter to further reduce artifacts in the reconstructed images. In the case of UNFOLD, we have analyzed the effect of relaxing the object stationarity assumption and have shown that it leads to an increase in motion artifacts.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Harsh K. Agarwal and Jerry L. Prince "Theoretical framework for analyzing MR imaging of dynamic objects using filters and downsamplers", Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 61441B (10 March 2006); https://doi.org/10.1117/12.653648
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Cited by 1 scholarly publication.
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KEYWORDS
Magnetic resonance imaging

Image filtering

Image restoration

Optical filters

Space operations

Data acquisition

Fourier transforms

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