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Abstract #0575

Deep convolutional framelet neural network for reference-free EPI ghost correction

Juyoung Lee1 and Jong Chul Ye1

1KAIST, Daejeon, Republic of Korea

Annihilating filter-based low rank Hankel matrix approach (ALOHA) was recently used as a reference-free ghost artifact correction method. Inspired by another discovery that convolutional neural network can be represented by Hankel matrix decomposition, here we propose a deep CNN for reference-free EPI ghost correction. Using real EPI experiments, we demonstrate that the proposed method effectively removes the ghost artifacts with much faster reconstruction time compared to the existing reference-free approaches.

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