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Efficient Tissue Discrimination during Surgical Interventions Using Hyperspectral Imaging

  • Conference paper
Book cover Information Processing in Computer-Assisted Interventions (IPCAI 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8498))

Abstract

A new hyperspectral imaging system has been designed for integration in the operating room to detect anatomical tissues hardly noticed by the surgeon’s naked eye. This LCTF-based spectral imaging system is operative over visible and near infrared range (400-1100 nm). After spectral calibration and spatial registration, the tricky process consists in reducing the huge amount of acquired data and removing redundancy without losing valuable information. Band transformation and selection methods are applied on both labeled and unlabeled tissues to extract relevant information to be displayed on surgeon’s RGB monitor. Visualization processing involving global and local contrast enhancement is then performed. To provide a reference for evaluation, surgeon’s perception of the scene is also simulated based on retina cell spectral responses. Experiments on pig ureter hyperspectral datasets reveal that band selection methods are the most effective on this type of intervention, providing sharp interpretation and accurate visualization of the biological tissues.

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Author information

Authors and Affiliations

  1. Laboratoire PRISME, IUT Bourges, Université d’Orléans, France

    Dorra Nouri & Yves Lucas

  2. Laboratoire PRISME, Polytech’ Orléans, Université d’Orléans, France

    Sylvie Treuillet

Authors
  1. Dorra Nouri
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  2. Yves Lucas
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  3. Sylvie Treuillet
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Editor information

Editors and Affiliations

  1. Centre for Medical Image Computing and Department of Computer Science, University College London, United Kingdom

    Danail Stoyanov

  2. Montreal Neurological Institute, McGill University, Montreal, Canada

    D. Louis Collins

  3. Graduate School of Engineering, The University of Tokyo, Japan

    Ichiro Sakuma

  4. Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada

    Purang Abolmaesumi

  5. Inserm/Université de Rennes 1, 2, Avenue du Pr. Léon Bernard, CS 34317, 35043, Rennes, France

    Pierre Jannin

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© 2014 Springer International Publishing Switzerland

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Nouri, D., Lucas, Y., Treuillet, S. (2014). Efficient Tissue Discrimination during Surgical Interventions Using Hyperspectral Imaging. In: Stoyanov, D., Collins, D.L., Sakuma, I., Abolmaesumi, P., Jannin, P. (eds) Information Processing in Computer-Assisted Interventions. IPCAI 2014. Lecture Notes in Computer Science, vol 8498. Springer, Cham. https://doi.org/10.1007/978-3-319-07521-1_28

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  • DOI: https://doi.org/10.1007/978-3-319-07521-1_28

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07520-4

  • Online ISBN: 978-3-319-07521-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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