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Proceedings Paper

A novel software assistant for the clinical analysis of MR spectroscopy with MeVisLab
Author(s): Bernd Merkel; Markus T. Harz; Olaf Konrad; Horst K. Hahn; Heinz-Otto Peitgen
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Paper Abstract

We present a novel software assistant for the analysis of multi-voxel 2D or 3D in-vivo-spectroscopy signals based on the rapid-prototyping platform MeVisLab. Magnetic Resonance Spectroscopy (MRS) is a valuable in-vivo metabolic window into tissue regions of interest, such as the brain, breast or prostate. With this method, the metabolic state can be investigated non-invasively. Different pathologies evoke characteristically different MRS signals, e.g., in prostate cancer, choline levels increase while citrate levels decrease compared to benign tissue. Concerning the majority of processing steps, available MRS tools lack performance in terms of speed. Our goal is to support clinicians in a fast and robust interpretation of MRS signals and to enable them to interactively work with large volumetric data sets. These data sets consist of 3D spatially resolved measurements of metabolite signals. The software assistant provides standard analysis methods for MRS data including data import and filtering, spatio-temporal Fourier transformation, and basic calculation of peak areas and spectroscopic metabolic maps. Visualization relies on the facilities of MeVisLab, a platform for developing clinically applicable software assistants. It is augmented by special-purpose viewing extensions and offers synchronized 1D, 2D, and 3D views of spectra and metabolic maps. A novelty in MRS processing tools is the side-by-side viewing ability of standard FT processed spectra with the results of time-domain frequency analysis algorithms like Linear Prediction and the Matrix Pencil Method. This enables research into the optimal toolset and workflow required to avoid misinterpretation and misapplication.

Paper Details

Date Published: 17 March 2008
PDF: 9 pages
Proc. SPIE 6915, Medical Imaging 2008: Computer-Aided Diagnosis, 69152R (17 March 2008); doi: 10.1117/12.772638
Show Author Affiliations
Bernd Merkel, MeVis Research (Germany)
Markus T. Harz, MeVis Research (Germany)
Olaf Konrad, MeVis Research (Germany)
Horst K. Hahn, MeVis Research (Germany)
Heinz-Otto Peitgen, MeVis Research (Germany)

Published in SPIE Proceedings Vol. 6915:
Medical Imaging 2008: Computer-Aided Diagnosis
Maryellen L. Giger; Nico Karssemeijer, Editor(s)

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