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Proceedings Paper

Fast unsupervised hot-spot detection in 1H-MR spectroscopic imaging data using ICA
Author(s): Markus T. Harz; Volker Diehl; Bernd Merkel; Burckhard Terwey; Heinz-Otto Peitgen
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Paper Abstract

Independent Component Analysis (ICA) is a blind source separation technique that has previously been applied to various time-varying signals. It may in particular be utilized to study 1H-MR spectroscopic imaging (MRSI) data. The work presented firstly investigates preprocessing and parameterization for ICA on simulated data to assess different strategies. We then applied ICA processing to 2D/3D brain and prostate MRSI data obtained from two healthy volunteers and 17 patients. We conducted a correlation analysis of the mixing and separating matrices resulting from ICA processing with maps obtained from metabolite quantitations in order to elucidate the relationship between quantitative and ICA results. We found that the mixing matrices corresponding to the estimated independent components highly correlate with the metabolite maps for some cases, and for others differ. We provide explanations and speculations for that and propose a scheme to utilize the knowledge for hot-spot detection. From our experience, ICA is much faster than the calculation of metabolic maps. Additionally, water and lipid contaminations are on the way removed from the data; the user needs not manually exclude spectroscopic voxels from processing or analysis. ICA results show hot spots in the data, even where quantitation-based metabolic maps are difficult to assess due to noisy data or macromolecule distortions.

Paper Details

Date Published: 27 March 2009
PDF: 8 pages
Proc. SPIE 7259, Medical Imaging 2009: Image Processing, 72591X (27 March 2009); doi: 10.1117/12.808122
Show Author Affiliations
Markus T. Harz, Fraunhofer MEVIS (Germany)
Volker Diehl, MR and PET Ctr. Bremen (Germany)
Bernd Merkel, Fraunhofer MEVIS (Germany)
Burckhard Terwey, MR and PET Ctr. Bremen (Germany)
Heinz-Otto Peitgen, Fraunhofer MEVIS (Germany)

Published in SPIE Proceedings Vol. 7259:
Medical Imaging 2009: Image Processing
Josien P. W. Pluim; Benoit M. Dawant, Editor(s)

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