Xiaodong Ma1,
Feng Huang2, Chun Yuan1, 3, George Randy
Duensing4, Hua Guo1
1Center
for Biomedical Imaging Research, Department of Biomedical Engineering, School
of Medicine, Tsinghua University, Beijing, China; 2Philips
Healthcare, Beijing, China; 3Department of Radiology, University
of Washington, Seattle, WA, United States; 4Philips Healthcare,
Gainesville, FL, United States
Since using all the calibration signals from images with different contrasts potentially provides more information of coil sensitivities, we propose to use multi-contrast information to enhance JSENSE. The same coil sensitivities as well as multiple contrast images are jointly reconstructed in the new model. Preliminary results demonstrated that the multi-contrast JSENSE algorithm with more accurate initialization results in images with improved quality, while costs no more computational time than original JSENSE algorithm