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Abstract #3320

Enhancing K-Space Methods for Quantitative Susceptibility Mapping by Exploiting Consistency in Cone Data

Yan Wen 1,2 , Yi Wang 2,3 , and Tian Liu 1

1 MedImageMetric LLC, New York, New York, United States, 2 Biomedical Engineering, Cornell University, Ithaca, New York, United States, 3 Radiology, Weill Cornell Medical College, New York, New York, United States

K-space QSM algorithms are computationally inexpensive and easy to implement. But their results usually contains streaking artifacts. Here, we introduce a method that can be applied to an existing k-space results to improve its accuracy and suppress streaking artifacts by constraining the energy of the data in the cone region to the energy of the data in non-cone region, and enforcing structure consistency with sophisticated prior data. This post-QSM method was tested on a gadolinium phantom and an in vivo human brain, and it demonstrated the suppression of streaking artifacts as well as the recovery of cone region data.

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