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A Reproducibility Study for Visual MRSI Data Analytics

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Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1182))

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Abstract

Magnetic Resonance Spectroscopy Imaging (MRSI) is a spectral imaging method that measures per voxel spectral information of chemical resonance, from which metabolite concentrations can be computed. In recent work, we proposed a system that uses coordinated views between image-space visualizations and visual representations of the spectral (or feature) space. Coordinated interaction allowed us to analyze all metabolite concentrations together instead of focusing only at single metabolites at a time [8]. In this paper, we want to relate our findings to different results reported in the literature. MRSI is particularly useful for tumor classification and measuring its infiltration of healthy tissue. We compare the metabolite compositions obtained in the various tissues of our data against the compositions reported by other brain tumor studies using a visual analytics approach. It visualizes the similarities in a plot obtained using dimensionality reduction methods. We test our data against various sources to test the reproducibility of the findings.

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Authors and Affiliations

  1. Westfälische Wilhelms-Universität Münster, Münster, Germany

    Muhammad Jawad, Vladimir Molchanov & Lars Linsen

Authors
  1. Muhammad Jawad
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  2. Vladimir Molchanov
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  3. Lars Linsen
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Corresponding author

Correspondence to Lars Linsen .

Editor information

Editors and Affiliations

  1. University of Lisbon, Lisbon, Portugal

    Ana Paula Cláudio

  2. University of Rennes 1, Rennes, France

    Kadi Bouatouch

  3. University of Genoa, Genoa, Italy

    Manuela Chessa

  4. Mines ParisTech, Paris, France

    Alexis Paljic

  5. Linnaeus University, Växjö, Sweden

    Andreas Kerren

  6. French Civil Aviation University (ENAC), Toulouse, France

    Christophe Hurter

  7. University Jean Monnet, Saint-Etienne, France

    Alain Tremeau

  8. University of Catania, Catania, Italy

    Giovanni Maria Farinella

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Jawad, M., Molchanov, V., Linsen, L. (2020). A Reproducibility Study for Visual MRSI Data Analytics. In: Cláudio, A., et al. Computer Vision, Imaging and Computer Graphics Theory and Applications. VISIGRAPP 2019. Communications in Computer and Information Science, vol 1182. Springer, Cham. https://doi.org/10.1007/978-3-030-41590-7_15

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  • DOI: https://doi.org/10.1007/978-3-030-41590-7_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-41589-1

  • Online ISBN: 978-3-030-41590-7

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