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Abstract #3974

Cascaded Convolutional Neural Network (CNN) for Reconstruction of Undersampled Magnetic Resonance (MR) Images

Taejoon Eo1, Yohan Jun1, Taeseong Kim1, Jinseong Jang1, and Dosik Hwang1

1Yonsei University, Seoul, Korea, Republic of

We propose cascaded CNN operating on k-space and image domain alternatively for reconstruction of undersampled MR images. Our cascaded CNN is capable of restoring most of detailed structures in the full-sampled image while sufficiently removing undersampling artifacts.

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