Improved Quantitative Susceptibility Mapping ( QSM ) with HEIDI


Journal article


F. Schweser, K. Sommer, A. Deistung, J. Reichenbach
2011

Semantic Scholar
Cite

Cite

APA   Click to copy
Schweser, F., Sommer, K., Deistung, A., & Reichenbach, J. (2011). Improved Quantitative Susceptibility Mapping ( QSM ) with HEIDI.


Chicago/Turabian   Click to copy
Schweser, F., K. Sommer, A. Deistung, and J. Reichenbach. “Improved Quantitative Susceptibility Mapping ( QSM ) with HEIDI” (2011).


MLA   Click to copy
Schweser, F., et al. Improved Quantitative Susceptibility Mapping ( QSM ) with HEIDI. 2011.


BibTeX   Click to copy

@article{f2011a,
  title = {Improved Quantitative Susceptibility Mapping ( QSM ) with HEIDI},
  year = {2011},
  author = {Schweser, F. and Sommer, K. and Deistung, A. and Reichenbach, J.}
}

Abstract

INTRODUCTION – Quantitative susceptibility mapping (QSM) is a novel imaging technique that determines tissue magnetic susceptibility from the phase of complex gradient-echo (GRE) data [1]. Due to the ill-posed nature of this inverse problem, regularization strategies are required to reduce streaking artifacts on the computed susceptibility maps. It has, for example, been proposed recently to incorporate edge information from GRE magnitude images into the inversion procedure [2,3]. Wharton and Bowtell [4] have, however, demonstrated that edge information may lead to artificial structures in susceptibility maps. This paper presents an improved QSM algorithm, Homogeneity Enabled Incremental Dipole Inversion (HEIDI), which utilizes a sophisticated problem-specific incremental inversion procedure and a priori information on the homogeneity of the susceptibility distribution rather than on its edges. MATERIALS AND METHODS – A priori information: Extraction of a priori information was based on the assumption that a small gradient of the background-corrected GRE phase images φ coincides with a small gradient of the magnetic susceptibility χ : z y x j j j , , , 0 0 = ≈ ∂ ⇒ ≈ ∂ χ φ . This assumption allows generating a binary mask M of





Follow this website


You need to create an Owlstown account to follow this website.


Sign up

Already an Owlstown member?

Log in