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.