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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