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Adaptive Sparse Recovery of Medical Images with Variational Approach – Preliminary Study for CT Stroke

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Information Technologies in Biomedicine, Volume 3

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 283))

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Abstract

Presented research was directed to effective signal recovery problem for computer-aided medical diagnosis. Extracted and visualized information covered in sensed data of imaging systems supports interpretation according to ”second look” procedure. The integrated framework of compressive sensing was used to optimize CT acute stroke diagnosis. Previously studied nonlinear approximation of the sparse signals in adjusted dictionaries was extended with variational approach to extract more precisely the content components. Proposed methodology adjusts optimized fidelity norms and regularizing priors to semantic question of image-based diagnosis. Preliminary experimental study was performed to provide selected proof-of-concept results for designed CT hypodensity extractors.

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Author information

Authors and Affiliations

  1. Faculty of Mathematics and Information Science, Warsaw University of Technology, Koszykowa 75, 00-662, Warszawa, Poland

    Artur Przelaskowski

Authors
  1. Artur Przelaskowski
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Correspondence to Artur Przelaskowski .

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Editors and Affiliations

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

    Ewa Piętka

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

    Jacek Kawa

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

    Wojciech Wieclawek

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Przelaskowski, A. (2014). Adaptive Sparse Recovery of Medical Images with Variational Approach – Preliminary Study for CT Stroke. In: Piętka, E., Kawa, J., Wieclawek, W. (eds) Information Technologies in Biomedicine, Volume 3. Advances in Intelligent Systems and Computing, vol 283. Springer, Cham. https://doi.org/10.1007/978-3-319-06593-9_14

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  • DOI: https://doi.org/10.1007/978-3-319-06593-9_14

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-06592-2

  • Online ISBN: 978-3-319-06593-9

  • eBook Packages: EngineeringEngineering (R0)

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