Meeting Banner
Abstract #1356

Deep Learning-Based Respiratory Navigator Echo (DLnav) for Robust Free-Breathing Abdominal MRI

Yuji Iwadate1, Atsushi Nozaki1, Shigeo Okuda2, Tetsuya Wakayama1, and Masahiro Jinzaki2
1Global MR Applications and Workflow, GE Healthcare Japan, Hino, Japan, 2Department of Radiology, Keio University School of Medicine, Tokyo, Japan

We propose a deep learning-based respiratory navigator (DLnav) technique which uses a convolutional neuronal network (CNN) for respiratory motion detection. The pencil-beam navigator signals were transferred to the real time processing unit including a CNN module and a diaphragm position value was calculated there. DLnav was incorporated into prospectively navigator-gated 3D SPGR and its performance was evaluated in the volunteer scan. DLnav resulted in good synchronization with actual respiratory motion and reduced motion-induced blurring with two different tracker positions.

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

Join Here