Abstract #2569
Estimating 3D deformable motion from a series of fast 2D MRI images with CLARET
Jason Brown 1 , Cihat Eldeniz 1 , Wolfgang Rehwald 2 , Brian Dale 3 , Hongyu An 1 , and David Lalush 1
1
Joint Department of Biomedical Engineering,
The University of North Carolina at Chapel Hill and
North Carolina State University, Chapel Hill, NC, United
States,
2
Siemens
Healthcare, Malvern, PA, United States,
3
Siemens
Healthcare, Cary, NC, United States
In this application, we effectively estimated
patient-specific 3D deformable motion from fast 2D MRI
images. CLARET is an image registration method that has
been used to relate a set of 2D images to a
corresponding set of 3D images. Using CLARET to predict
the 3D motion of a subject from a set of 2D projection
images has the potential to be used in MRI imaging of
dynamic processes. The results of the registration give
a motion estimate that reduced alignment error mean and
variance in 2D frames. We concluded that CLARET can be
used effectively in an MRI setting.
This abstract and the presentation materials are available to members only;
a login is required.
Join Here
