Jongyeon Lee1, Byungjai Kim1, Wonil Lee1, and HyunWook Park1
1Korean Advanced Institute of Science and Technology, Daejeon, Korea, Republic of
1Korean Advanced Institute of Science and Technology, Daejeon, Korea, Republic of
Our proposed motion correction method for multi-contrast
brain MRI utilizes the registration network for fast image alignment and the
multi-output network for motion correction of multi-contrast MR images. The
proposed framework successfully reduces motion artifacts of all contrasts.
Figure 1: a) An overview of the proposed method. The input images
can contain motion-free images and motion-corrupted images. The output images
are the motion-corrected images if the corresponding input images are
motion-corrupted, whereas the outputs are almost the same as the input images
if the corresponding input images are motion-free. b) The detailed framework of the proposed network with the network
hyperparameters.
Figure 3: Example images of the baseline experiment for a) the synthesized test data and b) the real motion data in T1w, T2w, and FLAIR correction cases.
SSIM and NRMSE scores are written on the motion-corrected images. For the real
motion test, the red and blue boxes highlight the performance of the proposed method.
