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Automatic Early Stroke Recognition Algorithm in CT Images

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Information Technologies in Biomedicine

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 7339))

Abstract

The subject of the reported study was automatic recognition of early ischemic stroke lesions in CT scans. Proposed extraction method was based on the investigated specificity of tissue texture features in hypothetical penumbra regions.

Prediction of such regions was estimated by initial hypodensity enhancement procedure. Block-oriented areas of selected brain tissue were analyzed in both source and multiscale-processed data domains. The extraction and selection of well differentiating features were fundamental effort to verify research hypothesis that acute ischemic tissue is noticeably altered in CT imaging. Moreover, various classifiers were examined on large feature data sets. Limitations and shortcomings caused by a class imbalance problem were considered. Experimental verification of designed and implemented recognition procedures is the main input of this paper.

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Author information

Authors and Affiliations

  1. Institute of Radioelectronics, Warsaw University of Technology, Nowowiejska 15/19, Warsaw, Poland

    Grzegorz Ostrek & Artur Przelaskowski

Authors
  1. Grzegorz Ostrek
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  2. Artur Przelaskowski
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Editor information

Editors and Affiliations

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

    Ewa Piętka  & Jacek Kawa  & 

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Ostrek, G., Przelaskowski, A. (2012). Automatic Early Stroke Recognition Algorithm in CT Images. In: Piętka, E., Kawa, J. (eds) Information Technologies in Biomedicine. Lecture Notes in Computer Science(), vol 7339. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31196-3_11

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  • DOI: https://doi.org/10.1007/978-3-642-31196-3_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31195-6

  • Online ISBN: 978-3-642-31196-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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