Anuj Sharma1, Samir D Sharma1, and Andrew J Wheaton1
1Magnetic Resonance, Canon Medical Research USA, Inc., Mayfield Village, OH, United States
1Magnetic Resonance, Canon Medical Research USA, Inc., Mayfield Village, OH, United States
We
propose a method for retrospective rigid-body motion correction that uses a
subset of imaging data to create a reference image. We demonstrate that the
proposed method reduces the reconstruction time by a factor of 2 over the
conventional method.
Figure
1: (a) Joint correction alternates between image
and motion estimation for all shots. (b) Incremental correction estimates the
initial image using shots with similar motion. Then motion for each shot is sequentially
estimated followed by image update. (c) Initial image used in incremental
correction has much lower artifacts than the initial image used in joint correction.
The final estimate in incremental correction provides the motion corrected
image.
Figure
2: Results from the simulation study. (a) iMoCo
was able to recover the image without significant residual artifacts, (b) Images
from joint correction were improved as the number of iterations were increased.
However, residual artifacts were seen (arrows) even after 80 iterations because
the solver had not converged as indicated by the data consistency error plot in
(c).
