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Abstract #3449

Quantitative Susceptibility Mapping by Using the Morphology Enabled Dipole Inversion (MEDI) Approach with a New Prior Information

Jianlei Liu1, 2, Tian Liu2, Shuai Wang3, Keigo Kawaji, 24, Yi Wang, 24

1XiDian University, Xi'an, Shaanxi, China; 2Radiology, Weill Cornell Medical College, New York, United States; 3University of Electronic Science and Technology of China; 4Biomedical Engineering, Cornell University, Ithaca, NY, United States


The morphology enabled dipole inversion with L1_norm (MEDI_L1) method use the structural information of magnitude image as prior information to uniquely determine the susceptibility distribution.The method can get desired results with high resolution of scanning. For low resolution of scanning, the MEDI_L1 is sensitive to the prior information. However, there are inconsistencies between the magnitude gradient and the gradient of the true susceptibility distribution.In this case, we use the structural information which comes from both magnitude image and relative difference field (RDF) image as prior information to improve the performance of MEDI_L1.