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Abstract #3600

Deep learning-based referenceless distortion correction for single-shot non-Cartesian spatiotemporally encoded MRI

Wei Wang1, Jian Wu1, Qinqin Yang1, Jian Han1, Congbo Cai1, Shuhui Cai1, and Zhong Chen1
1Xiamen University, Xiamen, China

Non-Cartesian spatiotemporally encoded MRI sequence shows obvious advantages in spatial Non-Cartesian spatiotemporally encoded MRI sequence shows obvious advantages in spatial selectivity and sampling efficiency. However, the resulting image is susceptible to severe distortion due to the cumulative effect of the B0 field inhomogeneity. In this work, this issue is addressed by introducing a deep learning-based method that is specifically tailored to inhomogeneous field correction. Simulation and in vivo rat brain experiments show that our method can effectively correct the image distortion and obtain the field map without extra reference scan.

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