Optimization of undersampled variable density spiral trajectories based on incoherence of spatial aliasing
نویسندگان
چکیده
Introduction: Variable density spiral (VDS) imaging typically samples low spatial frequencies densely and high spatial frequencies sparsely [1]. Reconstructed images are prone to aliasing artifacts, but they are considered to be acceptable in certain cases where aliasing of high spatial frequencies do not significantly deteriorate image quality. VDS imaging is particularly useful for dynamic MR applications such as cardiac imaging, where both high spatial and temporal resolution are desirable. However, unlike uniform density spiral (UDS) imaging, the VDS sampling density variation in k-space provides additional trajectory design parameters that have not, in the literature, been optimized in a systematic way. We identify the incoherency in spatial aliasing artifacts as an appropriate criterion for optimizing the trajectory design. Regularized iterative reconstruction is used to further reduce aliasing artifacts resulting from the “optimally” undersampled VDS trajectory [2]. We demonstrate the effectiveness of this approach in phantom studies. Theory: VDS sampling density denoted by field-of-view (FOV) is parameterized as a function of k-space radius: FOV(kr; {Fj}), where 0<kr<krmax, and {Fj} is a set of parameters that determine FOV. Timeoptimal k-space trajectories are designed using the density variation parameters {Fj} and krmax. The PSF is computed using direct Fourier transformation: , ) ( }) { ; ( 2
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