1Electrical Engineering, Stanford University, Stanford, CA, United States; 2Philips Healthcare, Shanghai, China; 3Department of Engineering Physics, Tsinghua University, Beijing, China; 4Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing, China; 5Department of Radiology, University of Washington, Seattle, WA, United States; 6Philips Healthcare, Gainesville, FL, United States
In this work, PROMISE (Parallel Reconstruction with Optimized acquisition for Multi-contrast Imaging in the context of compressed Sensing) is proposed to use manifold sharable information between multi-contrast scans for fast imaging. With the assumption that the same FOV is scanned for multi-contrast MRI, coil sensitivity maps, image structural information and optimal acquisition trajectory were extracted in seconds from previously acquired/reconstructed data to enhance the reconstruction of the following scans. Compared to previous work, PROMISE used more sharable information and resulted in lower artifact/noise level at higher reduction factors. Moreover, PROMISE is able to tolerate inter-scan motions better and is more clinically applicable.