Removal of lipid signal in mrsi using spatial-spectral constraints

Diego Hernando, Justin Haldar, Bradley Sutton, Zhi Pei Liang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Analysis and quantification of magnetic resonance spectroscopic imaging (MRSI) data is complicated by the presence of lipid nuisance signals in the spectra. These signals typically appear as peaks with amplitudes much larger than those of the metabolites of interest and, in the case of lipids, present broad, distorted lineshapes. Although the problem of lipid signal removal by postprocessing has been addressed in the past both in the context of single voxel spectroscopy (SVS) and MRSI, existing approaches use either spatial or spectral constraints to determine the lipid component in the signal. This paper introduces a method that incorporates both types of constraints for improved removal of lipid signals. Specifically, this method uses an anatomical image of the lipid locations to spatially constrain the lipid estimate as well as a field inhomogeneity map to improve spectral fitting of the lipid lineshape. Experimental results are shown to demonstrate the performance of the proposed method.

Original languageEnglish (US)
Title of host publication2007 4th IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro - Proceedings
Pages1360-1363
Number of pages4
DOIs
StatePublished - Nov 27 2007
Event2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro; ISBI'07 - Arlington, VA, United States
Duration: Apr 12 2007Apr 15 2007

Publication series

Name2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings

Other

Other2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro; ISBI'07
Country/TerritoryUnited States
CityArlington, VA
Period4/12/074/15/07

Keywords

  • Dixon imaging
  • Lipid removal
  • Magnetic resonance spectroscopic imaging
  • Papoulis-Gerchberg

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Medicine(all)

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