Yu Ding1, Mihaela Jekic1, Yiu-Cho
Chung2, Orlando P. Simonetti1
1The Ohio State University, Columbus,
OH, United States; 2Siemens Medical Solutions, Columbus, OH,
United States
TSENSE
and TGRAPPA are widely used parallel acquisition methods that can dynamically
update the sensitivity map to accommodate variations caused by physiological
motion. These methods use temporal low-pass filtering or sliding window
averaging to estimate a dynamically
changing sensitivity map. We propose to use the Karhunen-Loeve Transform
filter to generate a frame-by-frame estimate of the time-varying channel
sensitivity. In-vivo experiments showed that the new method significantly
reduces the artifact level in TGRAPPA reconstruction compared to traditional
approaches.