Affiliation:
1. Department of Electrical and Computer Engineering Cornell University Ithaca New York USA
2. Department of Radiology Weill Cornell Medicine New York New York USA
3. Meinig School of Biomedical Engineering Cornell University Ithaca New York USA
4. Department of Neurology Weill Cornell Medicine New York New York USA
Abstract
AbstractPurposeTo develop a tissue field‐filtering algorithm, called maximum spherical mean value (mSMV), for reducing shadow artifacts in QSM of the brain without requiring brain‐tissue erosion.Theory and MethodsResidual background field is a major source of shadow artifacts in QSM. The mSMV algorithm filters large field‐magnitude values near the border, where the maximum value of the harmonic background field is located. The effectiveness of mSMV for artifact removal was evaluated by comparing existing QSM algorithms in numerical brain simulation as well as using in vivo human data acquired from 11 healthy volunteers and 93 patients.ResultsNumerical simulation showed that mSMV reduces shadow artifacts and improves QSM accuracy. Better shadow reduction, as demonstrated by lower QSM variation in the gray matter and higher QSM image quality score, was also observed in healthy subjects and in patients with hemorrhages, stroke, and multiple sclerosis.ConclusionThe mSMV algorithm allows QSM maps that are substantially equivalent to those obtained using SMV‐filtered dipole inversion without eroding the volume of interest.
Funder
National Institutes of Health
National Multiple Sclerosis Society
Cited by
1 articles.
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