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Abstract #3844

An optimized slice-GRAPPA reconstruction method to reduce leakage artifacts in small-animal multiband imaging

Hiroshi Toyoda1, Sosuke Yoshinaga2, Naoya Yuzuriha2, Mitsuhiro Takeda2, and Hiroaki Terasawa2

1Center for Information and Neural Networks, National Institute of Information and Communications Technology, Suita, Japan, 2Department of Structural BioImaging, Kumamoto University, Kumamoto, Japan

Accurate slice separation for simultaneous multi-slice acquisition continues to be challenging, especially when animal scanners equipped with relatively few receiver coil elements are used. We propose an optimized slice-GRAPPA method to reconstruct the dual-band EPI of rat brains, in which the size-optimized kernel was iteratively estimated to reduce artifacts. The reconstructed images were evaluated in terms of inter-slice leakage, g-factor, and temporal variation across the repetitions. With the proposed method, inter-slice leakage artifacts and the g-factor were reduced, and the average signal-to-noise ratio was improved. Thus, the total reconstruction accuracy was improved in the multiband EPI in a small animal study.

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