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Deformable Models in Medical Image Segmentation

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3D Multiscale Physiological Human

Abstract

Today medical imaging techniques are very common and frequently used. To assist doctors and to perform automated analysis, the images have to be segmented by organ or region of interest. This segmentation process is a complex task. Relying on the image acquisition, segmentation approaches have to be robust and flexible enough to withstand low contrast, artifacts, small field of view and other phenomena caused by the reduction of acquisition time or dose of radiation. There is a general trend towards more specialized segmentation approaches, targeted at a limited set of organs and imaging parameters. Deformable Models are very commonly used and adapt to these requirements e.g. by exploiting prior knowledge, but require a good initialization. Different approaches, including the General Hough Transform and Registration methods will be considered.

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Notes

  1. 1.

    http://ktchu.serendipityresearch.org/software/lsmlib/index.html

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Acknowledgments

This work has been funded by the EU FP7 Marie Curie Initial Training Network project MultiScaleHuman (http://multiscalehuman.miralab.ch) under Grant No. 289897.

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Authors and Affiliations

  1. MIRALab, University of Geneva, Geneva, Switzerland

    Matthias Becker & Nadia Magnenat-Thalmann

  2. Institute for Media Innovation, Nanyang Technological University, 50 Nanyang Drive, Singapore, Singapore

    Nadia Magnenat-Thalmann

Authors
  1. Matthias Becker
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  2. Nadia Magnenat-Thalmann
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Correspondence to Matthias Becker .

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Editors and Affiliations

  1. Centre Universitaire Informatique, MIRALab - University of Geneva, Carouge, Geneve, Switzerland

    Nadia Magnenat-Thalmann

  2. Nuclear Medicine Division, University Hospital of Geneva, Geneva, Switzerland

    Osman Ratib

  3. Centre Universitaire Informatique, MIRALab - University of Geneva, Carouge, Geneve, Switzerland

    Hon Fai Choi

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Becker, M., Magnenat-Thalmann, N. (2014). Deformable Models in Medical Image Segmentation. In: Magnenat-Thalmann, N., Ratib, O., Choi, H. (eds) 3D Multiscale Physiological Human. Springer, London. https://doi.org/10.1007/978-1-4471-6275-9_4

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  • DOI: https://doi.org/10.1007/978-1-4471-6275-9_4

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