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Diffusion weighted images are usually acquired using 2D EPI methods. This technique has the limitation of low spatial resolution and low SNR. 3D diffusion weighted images are attractive option for improved SNR, however the motion-induced phase inconsistencies pose a challenge for the reconstruction of such data. We present a navigator-free phase-compensated reconstruction, which can be implemented as a regular parallel imaging framework. This two-step method involves first estimating a low-resolution phase from the data itself and then integrating the phase information in the forward encoding operator. We show good phase compensation from accelerated datasets using the proposed approach.
Lee et al. (Wed,) studied this question.
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