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Invariant Moments, Textural and Deep Features for Diagnostic MR and CT Image Retrieval

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Computer Analysis of Images and Patterns (CAIP 2021)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 13052))

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Abstract

Image analysis in the medical field aims to offer tools for the diagnosis and detection of life-threatening illness. This study means to propose a novel content-based image retrieval system oriented to medical diagnosis. In particular, we exploit several classic and deep image descriptors together with different similarity measures on three different data set, containing computed tomography and magnetic resonance images. Experiments show that feature selection can bring benefit if applied to deep and texture features, contrary to what observed for invariant moments. Moreover, the cityblock distance emerged to be quite suitable overall in this domain, although some other distances also exhibit satisfying robustness.

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Author information

Authors and Affiliations

  1. Department of Mathematics and Computer Science, University of Cagliari, via Ospedale 72, 09124, Cagliari, Italy

    Lorenzo Putzu, Andrea Loddo & Cecilia Di Ruberto

  2. Department of Electrical and Electronic Engineering, University of Cagliari, piazza d’Armi, 09123, Cagliari, Italy

    Andrea Loddo

Authors
  1. Lorenzo Putzu
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  2. Andrea Loddo
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  3. Cecilia Di Ruberto
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Corresponding author

Correspondence to Lorenzo Putzu .

Editor information

Editors and Affiliations

  1. Cyprus University of Technology, Limassol, Cyprus

    Nicolas Tsapatsoulis

  2. University of Cyprus, Nicosia, Cyprus

    Andreas Panayides

  3. University of Cyprus, Nicosia, Cyprus

    Theo Theocharides

  4. Cyprus University of Technology, Limassol, Cyprus

    Andreas Lanitis

  5. University of Cyprus, Nicosia, Cyprus

    Constantinos Pattichis

  6. University of Salerno, Salerno, Italy

    Mario Vento

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Putzu, L., Loddo, A., Ruberto, C.D. (2021). Invariant Moments, Textural and Deep Features for Diagnostic MR and CT Image Retrieval. In: Tsapatsoulis, N., Panayides, A., Theocharides, T., Lanitis, A., Pattichis, C., Vento, M. (eds) Computer Analysis of Images and Patterns. CAIP 2021. Lecture Notes in Computer Science(), vol 13052. Springer, Cham. https://doi.org/10.1007/978-3-030-89128-2_28

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  • DOI: https://doi.org/10.1007/978-3-030-89128-2_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-89127-5

  • Online ISBN: 978-3-030-89128-2

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