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Contextual Database of Radiological Images: Liver Parameters

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Innovations in Biomedical Engineering

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 526))

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Abstract

In this paper data from a contextual database of radiological images were analyzed in order to extract the parameters related to the volume and dimensions of the liver alongside with its intensity in the Magnetic Resonance Imaging (MRI) and Computed Tomography (CT). Pearson correlation of P = 0.99, p < 0.01 between mean value of pixels computed for the whole liver and for the biggest liver area in the 2D slice was obtained. High correlations (P = 0.71, p < 0.001) were received for the area of the largest 2D region of interest (ROI) and the overall volume of liver, independently of the image source. The results are even higher for CT studies only (P = 0.79, p = 0.001). The estimation of the whole liver parameters based on only one slice can significantly shorten the time needed for the preliminary diagnosis and help in the computer aided diagnosis (CAD) systems development.

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Acknowledgements

The work has been partially financed by Polish Ministry of Science and Silesian University of Technology statutory financial support for young researchers BKM-508/RAu-3/2016.

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Authors and Affiliations

  1. Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, Gliwice, Poland

    Paula Stępień

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

    Maria Bieńkowska & Jacek Kawa

Authors
  1. Paula Stępień
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  2. Maria Bieńkowska
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  3. Jacek Kawa
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Corresponding author

Correspondence to Paula Stępień .

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Editors and Affiliations

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

    Marek Gzik

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

    Ewaryst Tkacz

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

    Zbigniew Paszenda

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

    Ewa Piętka

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Stępień, P., Bieńkowska, M., Kawa, J. (2017). Contextual Database of Radiological Images: Liver Parameters. In: Gzik, M., Tkacz, E., Paszenda, Z., Piętka, E. (eds) Innovations in Biomedical Engineering. Advances in Intelligent Systems and Computing, vol 526. Springer, Cham. https://doi.org/10.1007/978-3-319-47154-9_28

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  • DOI: https://doi.org/10.1007/978-3-319-47154-9_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47153-2

  • Online ISBN: 978-3-319-47154-9

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