Abstract
Reconstruction from partial k-space data is an important issue in parallel magnetic resonance imaging (PMRI), as k-space undersampling during data acquisition is liable to produce artifacts in the image. In order to remove the image aliasing due to k-space undersampling, this paper presents a new finite impulse response (FIR) model of GRAPPA algorithm to replace the FIR model whose coefficients are fixed and currently used in GRAPPA image reconstruction methods. The proposed FIR model has been a better description for the correlation of k-space data and a better approximation for the inversion of parallel imaging process. The method is demonstrated using the proposed GRAPPA algorithm with in vivo free-breathing cardiac imaging data and the results show that this improved algorithm can greatly improve the image quality even at very high acceleration factor.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
