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Calculation of susceptibility through multiple orientation sampling (COSMOS): a method for conditioning the inverse problem from measured magnetic field map to susceptibility source image in MRI

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Liu, Tian, Spincemaille, Pascal, de Rochefort, Ludovic, Kressler, Bryan, Wang, Yi·2009·Magnetic Resonance in Medicine

Abstract

Magnetic susceptibility differs among tissues based on their contents of iron, calcium, contrast agent, and other molecular compositions. Susceptibility modifies the magnetic field detected in the MR signal phase. The determination of an arbitrary susceptibility distribution from the induced field shifts is a challenging, ill-posed inverse problem. A method called "calculation of susceptibility through multiple orientation sampling" (COSMOS) is proposed to stabilize this inverse problem. The field created by the susceptibility distribution is sampled at multiple orientations with respect to the polarization field, B(0), and the susceptibility map is reconstructed by weighted linear least squares to account for field noise and the signal void region. Numerical simulations and phantom and in vitro imaging validations demonstrated that COSMOS is a stable and precise approach to quantify a susceptibility distribution using MRI.

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Research works printed but not linked: 6

  1. Haacke EM, Brown RW, Thompson MR, Venkatesan R. Objects in external fields: the Lorentz sphere. Magnetic resonance imaging: phys- ical principles and sequence design. New York: Wiley-Liss; 1999. p 749 -757.
  2. Morgan J, Irarrazaval P. Efficient solving for arbitrary susceptibility distributions using residual difference fields. In: Proceedings of the 15th Annual Meeting of ISMRM, Berlin, Germany, 2007 (Abstract 35).
  3. Hanke M, Hansen PC. Regularization methods for large-scale problems. Surv Math Indust 1993;3:253-315.
  4. Moon TK, Stirling WC. Theory of the SVD. Mathematical methods and algorithms for signal processing. Upper Saddle River, NJ: Prentice Hall; 1999. p 369 -370.
  5. O'Handley RC. Quantum paramagnetism and diamagnetism. Modern magnetic materials principles and applications. New York: John Wiley & Sons; 2000. p 92, 492.
  6. Kressler B, de Rochefort L, Spincemaille P, Liu T, Wang Y. Estimation of sparse magnetic susceptibility distributions from MRI using non- linear regularization. In: Proceedings of the 16th Annual Meeting of ISMRM, Toronto, Ontario, Canada, 2008 (Abstract 1514).

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Authors
Liu, T., Spincemaille, P., de Rochefort, L., Kressler, B., & Wang, Y.
Affiliations
Cornell University (US)
Corresponding author
Wang, Yi
Venue
Magnetic Resonance in Medicine
Publisher
Wiley
Published
2008-12-18
Volume
61
Issue
1
Pages
196-204
ISSN
  • 0740-3194 (ISSN-L)
  • 1522-2594
OpenAlex
W2152374117
Cited by
454
References
34
Citations by year
2026: 10 · 2025: 19 · 2024: 20 · 2023: 21 · 2022: 29 · 2021: 34 · 2020: 42 · 2019: 33 · 2018: 22 · 2017: 24 · 2016: 27 · 2015: 31 · 2014: 36 · 2013: 35 · 2012: 21
FWCI
12.58
Type
journal article
Language
en
Open access
Locations
  • Magnetic Resonance in Medicine (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
  • Physical Sciences › Physics and Astronomy › Nuclear and High Energy Physics › NMR spectroscopy and applications
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
Keywords
magnetic susceptibility mapping, cosmos, ill-posed inverse problems, phase-contrast MRI, magnetic field mapping, weighted least squares, field noise, iron and calcium content
MeSH terms
Algorithms, Computer Simulation, Humans, Image Enhancement, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Magnetics, Models, Biological, Sensitivity and Specificity, Reproducibility of Results, Phantoms, Imaging

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