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2015 | 5 | 139--143
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A Two-Level Classifier for Automatic Medical Objects Classification

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The goal of this paper is to describe the approach for automatic identifying human organs from a medical CT images and discuss results of its comparison to different classification methods. The main premise of this approach is the use of data sets together with the relevant domain knowledge. We test our approach on multiple CT images of chest organs (trachea, lungs, bronchus) and demonstrate usefulness and effectiveness of the resulting classifications. The presented approach can be used to assist in solving more complex medical problems. (original abstract)
Opis fizyczny
  • Interdisciplinary Centre for Computational Modelling, University of Rzeszów, Poland
  • Radiology consultant, Department of Pulmonology, Pulmonary Hospital,, Poland
  • II Department of Internal Medicine, Jagiellonian University Medical College, Kraków, Poland
  • A. Przelaskowski, T. Podsiadly-Marczykowska, A. Wroblewska, P. Boninski, and P. Bargiel, "Computer-aided interpretation of medical images: Mammography case study," MG&V, vol. 16, no. 3, pp. 347-375, Jan. 2007. [Online]. Available: id=1993447.1993457
  • S. Nguyen, H., "Approximate boolean reasoning: Foundations and applications in data mining," LNCS Transactions on Rough Sets V, vol. 4100, pp. 334-506, 2006.
  • G. Bazan. J., S. Nguyen, H., H. Nguyen, S., P. Synak, and J. Wróblewski, "Rough set algorithms in classification problems," in Rough Set Methods and Applications: New Developments in Knowledge Discovery in Information Systems, ser. Studies in Fuzziness and Soft Computing, L. Polkowski, T. Y. Lin, and S. Tsumoto, Eds. Heidelberg, Germany: Springer-Verlag/Physica-Verlag, 2000, vol. 56, pp. 49-88.
  • A. Meyer-Baese and V. Schmid, "Chapter 2 - feature selection and extraction," in Pattern Recognition and Signal Analysis in Medical Imaging (Second Edition), second edition ed., A. Meyer-Baese and V. Schmid, Eds. Oxford: Academic Press, 2014, pp. 21 - 69. ISBN 978-0-12-409545-8
  • J. Cytowski, J. Gielecki, and A. Gola, Digital Medical Imaging. Theory. Algorithms. Applications, ser. Problemy Współczesnej Nauki: Informatyka. Akademicka Oficyna Wydawnicza EXIT, 2008. ISBN 9788360434482 In Polish.
  • A. Przelaskowski, "The role of sparse data representation in semantic image understanding," in Computer Vision and Graphics, ser. Lecture Notes in Computer Science, L. Bolc, R. Tadeusiewicz, L. Chmielewski, and K. Wojciechowski, Eds. Springer Berlin Heidelberg, 2010, vol. 6374, pp. 69-80. ISBN 978-3-642-15909-1. [Online]. Available:
  • M. R. Ogiela and R. Tadeusiewicz, Modern Computational Intelligence Methods for the Interpretation of Medical Images, ser. Studies in Computational Intelligence. Springer, 2008, vol. 84. ISBN 978-3-540- 75399-5
  • M. Kobashi and L. G. Shapiro, "Knowledge-based organ identification from ct images," Pattern Recognition, vol. 28, no. 4, pp. 475 - 491, 1995. doi:
  • C. A. Harlow and S. A. Eisenbeis, "The analysis of radiographic images," Computers, IEEE Transactions on, vol. C-22, no. 7, pp. 678- 689, July 1973. doi: 10.1109/TC.1973.5009135
  • P. Selfridge, Reasoning about Success and Failure in Aerial Image Understanding, ser. Reports // ROCHESTER UNIV NY. University of Rochester. Department of Computer Science, 1981.
  • G. Bazan, J. and M. Szczuka, "The Rough Set Exploration System," Transactions on Rough Sets, vol. 3400, no. 3, pp. 37-56, 2005.
  • P. Pardel, J. Bazan, J. Zarychta, and S. Bazan-Socha, "Automatic medical objects classification based on data sets and domain knowledge," in Beyond Databases, Architectures and Structures, ser. Communications in Computer and Information Science, S. Kozielski, D. Mrozek, P. Kasprowski, B. Małysiak-Mrozek, and D. Kostrzewa, Eds. Springer International Publishing, 2015, vol. 521, pp. 415-424. ISBN 978-3-319-18421-0. [Online]. Available: 1007/978-3-319-18422-7_37
  • M. Hall, E. Frank, G. Holmes, B. Pfahringer, P. Reutemann, and I. H. Witten, "The weka data mining software: An update," SIGKDD Explor. Newsl., vol. 11, no. 1, pp. 10-18, Nov. 2009. doi: 10.1145/1656274.1656278. [Online]. Available: 1145/1656274.1656278
  • A. Niimi, H. Matsumoto, M. Takemura, T. Ueda, Y. Nakano, and M. Mishima, "Clinical assessment of airway remodeling in asthma," Clinical Reviews in Allergy And Immunology, vol. 27, no. 1, pp. 45-57, 2004. doi: 10.1385/CRIAI:27:1:045
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