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Automatic Medical Objects Classification Based on Data Sets and Domain Knowledge

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Beyond Databases, Architectures and Structures (BDAS 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 521))

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Abstract

This paper describes the approach for automatic identifying organs from a medical CT imagery. Main assumption of this approach is the use of data sets and domain knowledge. We apply this approach to automatic classification of chest organs (trachea, lungs, bronchus) and present the results to demonstrate their usefulness and effectiveness. The paper includes the results of experiments that have been performed on medical data obtained from II Department of Internal Medicine, Jagiellonian University Medical College, Krakow, Poland. The experimental results showed that the approach is promising and can be used in the future to support solving more complex medical problems.

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Correspondence to Przemyslaw Wiktor Pardel .

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Pardel, P.W., Bazan, J.G., Zarychta, J., Bazan-Socha, S. (2015). Automatic Medical Objects Classification Based on Data Sets and Domain Knowledge. In: Kozielski, S., Mrozek, D., Kasprowski, P., Małysiak-Mrozek, B., Kostrzewa, D. (eds) Beyond Databases, Architectures and Structures. BDAS 2015. Communications in Computer and Information Science, vol 521. Springer, Cham. https://doi.org/10.1007/978-3-319-18422-7_37

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  • DOI: https://doi.org/10.1007/978-3-319-18422-7_37

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-18421-0

  • Online ISBN: 978-3-319-18422-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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