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Application of Fuzzy Image Concept to Medical Images Matching

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Information Technology in Biomedicine (ITIB 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 762))

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Abstract

The main aim of this research is presenting an automated image matching methodology being used in the field of medicine for inter- and intraobjectional image matching. This paper shows a different approach avoiding the standard procedures associated with performing four main steps of the registration process: feature detection, feature matching, mapping function design and image transformation with resampling, and replacing them with the fuzzy image concept combined with the use of similarity measures. This methodology has been implemented in MATLAB and tested on clinical T1- and T2-weighted magnetic resonance imaging (MRI) slices of the knee joint in coronal and sagittal plane.

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Acknowledgement

This research was supported by Silesian University of Technology, Faculty of Biomedical Engineering statutory financial support No. BK-209/RIB1/2018 (07/010/BK_18/0021).

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Authors and Affiliations

  1. Faculty of Biomedical Engineering, Silesian University of Technology, Roosevlta 40, Zabrze, Poland

    Piotr Zarychta

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  1. Piotr Zarychta
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Correspondence to Piotr Zarychta .

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Editors and Affiliations

  1. Faculty of Biomedical Engineering, Silesian University of Technology, Zabrze, Poland

    Ewa Pietka

  2. Faculty of Biomedical Engineering, Silesian University of Technology, Zabrze, Poland

    Pawel Badura

  3. Faculty of Biomedical Engineering, Silesian University of Technology, Zabrze, Poland

    Jacek Kawa

  4. Faculty of Biomedical Engineering, Silesian University of Technology, Zabrze, Poland

    Wojciech Wieclawek

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Zarychta, P. (2019). Application of Fuzzy Image Concept to Medical Images Matching. In: Pietka, E., Badura, P., Kawa, J., Wieclawek, W. (eds) Information Technology in Biomedicine. ITIB 2018. Advances in Intelligent Systems and Computing, vol 762. Springer, Cham. https://doi.org/10.1007/978-3-319-91211-0_3

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