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Abstract #0226

Joint Reconstruction of MR Image and Coil Sensitivity Maps using Deep Model-based Network

Yohan Jun1, Hyungseob Shin1, Taejoon Eo1, and Dosik Hwang1
1Electrical and Electronic Engineering, Yonsei University, Seoul, Korea, Republic of

We propose a Joint Deep Model-based MR Image and Coil Sensitivity Reconstruction Network (Joint-ICNet), which jointly reconstructs an MR image and coil sensitivity maps from undersampled multi-coil k-space data using deep learning networks combined with MR physical models. Joint-ICNet has two blocks, where one is an MR image reconstruction block that reconstructs an MR image from undersampled k-space data and the other is a coil sensitivity reconstruction block that estimates coil sensitivity from undersampled k-space data. The desired MR image and coil sensitivity maps can be obtained by sequentially estimating them with two blocks based on the unrolled network architecture.

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