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Abstract #3239

Comprehensive CG-SENSE reconstruction of SMS-EPI

Lucilio Cordero-Grande1, Anthony Price1, Jana Hutter1, Emer Hughes1, and Joseph V. Hajnal1

1Center for the Developing Brain, King's College London, London, United Kingdom

A 2D CG-SENSE framework is proposed aiming at an integrated treatment of the main error sources in SMS-EPI reconstruction. Our pipeline jointly estimates the sensitivity profiles, Nyquist ghosting parameters, and image to be unfolded. In addition, an artifact-SNR tradeoff is established at a pixel level. Assessment by a phantom experiment has shown that all the main functionalities of the method do help diminish reconstruction artifacts. Stable results have been obtained when applying the framework in a large cohort of motion corrupted fMRI and DWI neonatal studies.

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