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International Conference on Computer Vision, Imaging and Computer Graphics

VISIGRAPP 2013: Computer Vision, Imaging and Computer Graphics -- Theory and Applications pp 50–65Cite as

Data-Aware Picking for Medical Models

Part of the Communications in Computer and Information Science book series (CCIS,volume 458)

Abstract

Medical doctors are often faced with the problem of selecting anchoring points in 3D space. These points are commonly used for measurement tasks, such as lengths of bones, or dimensions of pathological structures (e.g. tumours). Since previous research indicates that measurement tasks can be usually carried out more efficiently in VR environments than in desktop-based systems, we have concentrated on the development of selection tools for medical models. These models have a set of particularities such as the presence of semi-transparencies, and there is a lack of tools for measurement support for such models in VR environments. Our VR-based interaction technique uses the data to automatically generate candidate anchor points, and it is specially focused on the efficient selection of 3D points in datasets rendered using methods with semi-transparency such as Direct Volume Rendering. We will show that our method is effective, precise, and reduces the time and amount of movements required to set the anchor points as compared with other classical techniques based on clipping planes. We also provide a couple of improvements tailored to reduce the inherent imprecision of 3D devices due to hand vibration, and the flexibility in transfer function selection for anchor point definition.

Keywords

  • 3D interaction
  • 3D selection
  • Medical visualization
  • Virtual reality

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Acknowledgements

The authors want to thank all the participants involved in the user study. This work has been supported by the project TIN2010-20590-C01-01 of the Spanish Government.

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Authors and Affiliations

  1. ViRVIG-LSI, Universitat Politècnica de Catalunya, C. Jordi Girona 1–3, Edif. Omega, 08034, Barcelona, Spain

    Eva Monclús, Pere-Pau Vázquez & Isabel Navazo

Authors
  1. Eva Monclús
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  2. Pere-Pau Vázquez
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  3. Isabel Navazo
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Corresponding author

Correspondence to Eva Monclús .

Editor information

Editors and Affiliations

  1. Università di Catania, Catania, Catania, Italy

    Sebastiano Battiato

  2. Inria/ZIRST, Saint Ismier, France

    Sabine Coquillart

  3. Swansea University, Swansea, United Kingdom

    Robert S. Laramee

  4. Linnaeus University, Växjö, Sweden

    Andreas Kerren

  5. Escola Superior de Tecnologia do IPS, Setúbal, Portugal

    José Braz

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Monclús, E., Vázquez, PP., Navazo, I. (2014). Data-Aware Picking for Medical Models. In: Battiato, S., Coquillart, S., Laramee, R., Kerren, A., Braz, J. (eds) Computer Vision, Imaging and Computer Graphics -- Theory and Applications. VISIGRAPP 2013. Communications in Computer and Information Science, vol 458. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44911-0_4

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  • DOI: https://doi.org/10.1007/978-3-662-44911-0_4

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