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Novel Edge Detection Scheme in the Trinion Space for Use in Medical Images with Multiple Components

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Computational Collective Intelligence (ICCCI 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9876))

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Abstract

Very recently we proposed a promising scheme for tissue classification of multi-parametric magnetic resonance images (MP-MRI) of the brain based on signal analysis in higher dimensional vector spaces. The method treats MP-MR images as colors represented holistically in three (trinion) or four (quaternion) algebraic spaces. Compared to the well known quaternions, the recently proposed three component trinions are more efficient in representation of images with three channels and the respective Fourier transforms allow visualization of their wavenumber spectra as a whole. The current study discusses an edge detection scheme based on statistical metrics derived from locally computed trinion Fourier transforms for use in robust edge detection of MP-MR images and other color medical images. Performance of the proposed scheme is compared against a quaternion formulation and with another vectorial approach. Application of the method is shown in edge detection of various color test images and scenes with different degrees of difficulty. Discussion and preliminary results on the application of the proposed scheme on MP-MR images of brain scans of patients treated for glioblastoma multiforme (GBM) have also been included.

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Acknowledgements

This work was supported by the project “Smart Solutions for Ubiquitous Computing Environments” FIM (ID: UHK-FIM-SP-2016-2102), University of Hradec Kralove, Czech Republic.

Author information

Authors and Affiliations

  1. Center of Biomedical Engineering, Division of Biomedical Computing, Addis Ababa Institute of Technology, Addis Ababa University, Addis Ababa, Ethiopia

    Dawit Assefa

  2. Center for Basic and Applied Research, Faculty of Informatics and Management, University of Hradec Kralove, Hradec Kralove, Czech Republic

    Dawit Assefa & Ondrej Krejcar

Authors
  1. Dawit Assefa
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  2. Ondrej Krejcar
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Corresponding author

Correspondence to Ondrej Krejcar .

Editor information

Editors and Affiliations

  1. Wroclaw University of Technology , Wroclaw, Poland

    Ngoc Thanh Nguyen

  2. Aristotle University of Thessaloniki , Thessaloniki, Greece

    Lazaros Iliadis

  3. Department of Forestry and Manageme, Democritus University of Thrace Department of Forestry and Manageme, Orestiada Thrace, Greece

    Yannis Manolopoulos

  4. Wrocław University of Technology , Wrocław, Poland

    Bogdan Trawiński

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Assefa, D., Krejcar, O. (2016). Novel Edge Detection Scheme in the Trinion Space for Use in Medical Images with Multiple Components. In: Nguyen, N., Iliadis, L., Manolopoulos, Y., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2016. Lecture Notes in Computer Science(), vol 9876. Springer, Cham. https://doi.org/10.1007/978-3-319-45246-3_22

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  • DOI: https://doi.org/10.1007/978-3-319-45246-3_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-45245-6

  • Online ISBN: 978-3-319-45246-3

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