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Annual Conference on Medical Image Understanding and Analysis

MIUA 2017: Medical Image Understanding and Analysis pp 123–132Cite as

Tissues Classification of the Cardiovascular System Using Texture Descriptors

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 723))

Abstract

In this paper, we present an approach to automatically classify tissues of the cardiovascular system using texture information. Additionally, this process makes possible to identify some cardiovascular organs, since some tissues belong to muscles associated to those, i.e. identifying the tissue makes possible to identify the organ. We have assessed rotation invariant Local Binary Patterns (LBPri) and Haralick features to describe the content of histological images. We also assessed Random Forest (RF) and Linear Discriminant Analysis (LDA) for the classification of these descriptors. The tissues were classified into four classes: (i) cardiac muscle of the heart, (ii) smooth muscle of the elastic artery, (iii) loose connective tissue, and (iv) smooth muscle of the large vein and the elastic artery. The experimental validation is conducted with a set of 2400 blocks of \(100\times 100\) pixels each. The classifier was assessed using a 10-fold cross-validation. The best AUCs (0.9875, 0.9994 and 0.9711 for the cardiac muscle of the heart, the smooth muscle of muscular artery, the smooth muscle of the large vein and the elastic artery classes, respectively) are achieved by LBPri and RF.

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Acknowledgements

This work has been supported by COLCIENCIAS and Asociación Universitaria Iberoamericana de Postgrado, AUIP. We thank Liliana Salazar, M.Sc., for providing insight and expertise that greatly assisted the research.

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Authors and Affiliations

  1. Computer and Systems Engineering School, University of Valle, Cali, Colombia

    Claudia Mazo & Maria Trujillo

  2. Industrial and Informatics Engineering School, University of León, León, Spain

    Enrique Alegre & Víctor González-Castro

Authors
  1. Claudia Mazo
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  2. Enrique Alegre
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  3. Maria Trujillo
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  4. Víctor González-Castro
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Corresponding author

Correspondence to Claudia Mazo .

Editor information

Editors and Affiliations

  1. Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, United Kingdom

    María Valdés Hernández

  2. University of León, León, Spain

    Víctor González-Castro

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Mazo, C., Alegre, E., Trujillo, M., González-Castro, V. (2017). Tissues Classification of the Cardiovascular System Using Texture Descriptors. In: Valdés Hernández, M., González-Castro, V. (eds) Medical Image Understanding and Analysis. MIUA 2017. Communications in Computer and Information Science, vol 723. Springer, Cham. https://doi.org/10.1007/978-3-319-60964-5_11

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  • DOI: https://doi.org/10.1007/978-3-319-60964-5_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60963-8

  • Online ISBN: 978-3-319-60964-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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