Meeting Banner
Abstract #1361

Motion Correction and Registration Networks for Multi-Contrast Brain MRI

Jongyeon Lee1, Byungjai Kim1, Wonil Lee1, and HyunWook Park1
1Korean Advanced Institute of Science and Technology, Daejeon, Korea, Republic of

Deep learning techniques have been applied to motion artifact correction without motion estimation or tracking. We previously studied the motion correction method for the multi-contrast brain MRI using NMI maximization and the multi-input neural network. However, as the previous work suffered from a prolonged alignment time and a training inconvenience, we adopt the registration network to reduce alignment time and the multi-output neural network to be trained only once. Our proposed method successfully reduces motion artifacts in the multi contrast images.

This abstract and the presentation materials are available to members only; a login is required.

Join Here