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Abstract #2637

Multi-Contrast JSENSE

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