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Abstract #4695

Convolutional Neural Networks with Aliasing Layers for Correcting Parallel Imaging and EPI Ghost Artifacts

Hidenori Takeshima1

1Advanced Technology Research Department, Research and Development Center, Canon Medical Systems Corporation, Yokohama, Japan

The author proposes a new layer named aliasing layer (AL) for effectively correcting MR-specific aliasing artifacts using convolutional neural networks. In MR images acquired using parallel imaging (PI) and/or echo-planar imaging (EPI), the locations of aliasing artifacts and/or N/2 ghost artifacts can be analytically calculated. The AL preprocesses MR images by moving the calculated locations to the locations accessible through summations over all channels in a convolution layer. The experimental results demonstrate that the correction method using the proposed AL could effectively remove PI aliasing and EPI ghosting artifacts.

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