Abstract #1570
Acceleration of Perfusion MRI using Adaptive Artificial Sparsity
Xiaoying Cai 1 , Feng Huang 2 , Kui Ying 3 , Chun Yuan 4 , and Huijun Chen 4
1
Biomedical Engineering, University of
Virginia, Charlottesville, Virginia, United States,
2
Philips
Healthcare, Gainesville, FL, United States,
3
Department
of Engineering Physics, Tsinghua University, Beijing,
China,
4
Center
for Biomedical Imaging Research, Beijing, China
We proposed a new framework for reconstruction of
accelerating perfusion imaging. By prediction intensity
change of perfusion images using pre-contrast image and
adaptive weights , the sparsity of dynamic images was
strengthened, which benefits the following regular
imaging reconstruction (k-t GRAPPA, k-t PCA or k-t SLR).
The framework was tested with black blood vessel wall
imaging data. The results showed that our new framework
could result in better image reconstruction and improved
kinetic parameter fitting for all tested reconstruction
methods when acceleration factors were high.
How to access this content:
For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.
After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.
After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.
Click here for more information on becoming a member.
