Aliasing Layer: A New Method for Removing Parallel Imaging Aliasing and EPI Ghosting Artifacts in CNN [Presidential Award Proceedings]
Hidenori Takeshima · Japanese Journal of Magnetic Resonance in Medicine · 2021
Purpose : Residual aliasing artifacts are often generated in MR images acquired using parallel imaging (PI) and/or echo-planar imaging (EPI). Existing denoising methods based on convolutional neural networks (CNNs) assume that an image has spatial locality. Since the artifacts do not satisfy the assumption of CNNs, denoising methods based on CNNs cannot remove artifacts efficiently. In this presentation, the author proposes a new method that can significantly reduce residual aliasing artifacts. The proposed method utilizes the locations of aliasing artifacts and/or N-half ghost artifacts, which can be analytically calculated.