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Stroke Tissue Pattern Recognition Based on CT Texture Analysis

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Proceedings of the 9th International Conference on Computer Recognition Systems CORES 2015

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 403))

Abstract

The main objective of this paper is a texture-based solution to the problem of acute stroke tissue recognition on computed tomography images. Our proposed method of early stroke indication was based on two fundamental steps: (i) segmentation of potential areas with distorted brain tissue (selection of regions of interest), and (ii) acute stroke tissue recognition by extracting and then classifying a set of well-differentiating features. The proposed solution used various numerical image descriptors determined in several image transformation domains: 2D Fourier domain, polar 2D Fourier domain, and multiscale domains (i.e., wavelet, complex wavelet, and contourlet domain). The obtained results indicate the possibility of relatively effective detection of early stroke symptoms in CT images. Selected normal or pathological blocks were classified by LogitBoost with the accuracy close to 75 % with the use of our adjusted cross-validation procedure.

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Notes

  1. 1.

    Calculated with DBM MRMC 2.5 software tool.

  2. 2.

    Definition of measures: \(Accuracy=\frac{TP+TN}{N_{pos}+N_{neg}}\), \(Sensitivity=\frac{TP}{N_{pos}}\), \(Specificity=\frac{TN}{N_{neg}}\), \(Precision=\frac{TP}{TP+FP}\).

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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, ul. Koszykowa 75, 00-662, Warsaw, Poland

    Grzegorz Ostrek, Artur Nowakowski & Artur Przelaskowski

  2. Institute of Radioelectronics, Warsaw University of Technology, ul. Nowowiejska 15/19, 00-665, Warsaw, Poland

    Magdalena Jasionowska

  3. Department of Dental and Maxillofacial Radiology, Faculty of Medicine and Dentistry, Medical University of Warsaw, ul. Nowogrodzka 59, 02-006, Warsaw, Poland

    Kazimierz Szopiński

Authors
  1. Grzegorz Ostrek
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  2. Artur Nowakowski
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  3. Magdalena Jasionowska
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  4. Artur Przelaskowski
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  5. Kazimierz Szopiński
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Corresponding author

Correspondence to Grzegorz Ostrek .

Editor information

Editors and Affiliations

  1. Department of Systems, Wrocław University of Technology, Wroclaw, Poland

    Robert Burduk

  2. Department of Systems and Computer, Wrocław University of Technology, Wroclaw, Poland

    Konrad Jackowski

  3. Department of Systems and Computer, Wrocław University of Technology, Wroclaw, Poland

    Marek Kurzyński

  4. Dept. of Systems and Computer Networks, Wrocław University of Technology, Wroclaw, Poland

    Michał Woźniak

  5. Department of Systems, Wrocław University of Technology, Wroclaw, Poland

    Andrzej Żołnierek

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Ostrek, G., Nowakowski, A., Jasionowska, M., Przelaskowski, A., Szopiński, K. (2016). Stroke Tissue Pattern Recognition Based on CT Texture Analysis. In: Burduk, R., Jackowski, K., Kurzyński, M., Woźniak, M., Żołnierek, A. (eds) Proceedings of the 9th International Conference on Computer Recognition Systems CORES 2015. Advances in Intelligent Systems and Computing, vol 403. Springer, Cham. https://doi.org/10.1007/978-3-319-26227-7_8

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  • DOI: https://doi.org/10.1007/978-3-319-26227-7_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26225-3

  • Online ISBN: 978-3-319-26227-7

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