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Conference of Information Technologies in Biomedicine

ITiB 2016: Information Technologies in Medicine pp 119–135Cite as

Targeted X-Ray Computed Tomography: Compressed Sensing of Stroke Symptoms

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 471))

Abstract

The subject of reported research is model-based compressed sensing applied to CT imaging. Personalized CT examinations were designed according to requirements of CT-based stroke diagnosis in emergency care. Adaptive sensing was optimized to recover more accurately diagnostic information which is partially hidden or overlooked in standard procedures. In addition, limited number of measurements was used to reduce radiation dose. As a result, new paradigm of integrated optimization for CT system was proposed. Formalized diagnostic model is used to improve the relevance of CT imaging in emergency diagnosis. Simulated experiments confirmed a proof of concept realization.

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Acknowledgments

This publication was funded by the National Science Centre (Poland) based on the decision DEC-2011/03/B/ST7/03649.

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Authors and Affiliations

  1. Faculty of Mathematics and Information Science, Warsaw University of Technology, Koszykowa 75, Warszawa, Poland

    Artur Przelaskowski

Authors
  1. Artur Przelaskowski
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Correspondence to Artur Przelaskowski .

Editor information

Editors and Affiliations

  1. Fac of Biomed Engg, ul. Roosevelta 40, Silesian University of Technology, Gliwice, Poland

    Ewa Piętka

  2. Fac of Biomed Engg, ul. Roosevelta 40, Silesian University of Technology, Gliwice, Poland

    Pawel Badura

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

    Jacek Kawa

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

    Wojciech Wieclawek

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© 2016 Springer International Publishing Switzerland

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Przelaskowski, A. (2016). Targeted X-Ray Computed Tomography: Compressed Sensing of Stroke Symptoms. In: Piętka, E., Badura, P., Kawa, J., Wieclawek, W. (eds) Information Technologies in Medicine. ITiB 2016. Advances in Intelligent Systems and Computing, vol 471. Springer, Cham. https://doi.org/10.1007/978-3-319-39796-2_11

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  • DOI: https://doi.org/10.1007/978-3-319-39796-2_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-39795-5

  • Online ISBN: 978-3-319-39796-2

  • eBook Packages: EngineeringEngineering (R0)

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