Intravoxel Incoherent Motion (IVIM) parameter mapping yields quantitative information about diffusion and pseudo-perfusion properties. In brain IVIM, parallel imaging with two-fold undersampling has been reported. In order to address noise amplification and unfolding artifacts at undersampling factors greater than two with parallel imaging, reconstruction in spatio-principal component space with data reshuffling (k-bpp PCA) is presented here. Using in-vivo brain data, it is demonstrated that k-bpp PCA allows for significantly increased undersampling factors relative to parallel imaging while maintaining comparable image quality and parameter estimation errors.
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