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Multi-Atlas-Based Segmentation of Pelvic Structures from CT Scans for Planning in Prostate Cancer Radiotherapy

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Abdomen and Thoracic Imaging

Abstract

In prostate cancer radiotherapy, the accurate identification of the prostate and organs at risk in planning computer tomography (CT) images is an important part of the therapy planning and optimization. Manually contouring these organs can be a time-consuming process and subject to intra- and inter-expert variability. Automatic identification of organ boundaries from these images is challenging due to the poor soft tissue contrast. Atlas-based approaches may provide a priori structural information by propagating manual expert delineations to a new individual space; however, the interindividual variability and registration errors may lead to biased results. Multi-atlas approaches can partly overcome some of these difficulties by selecting the most similar atlases among a large data base, but the definition of similarity measure between the available atlases and the query individual has still to be addressed. The purpose of this chapter is to explain atlas-based segmentation approaches and the evaluation of different atlas-based strategies to simultaneously segment prostate, bladder, and rectum from CT images. A comparison between single and multiple atlases is performed. Experiments on atlas ranking, selection strategies, and fusion-decision rules are carried out to illustrate the presented methodology. Propagation of labels using two registration strategies is applied and the results of the comparison with manual delineations are reported.

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Author information

Authors and Affiliations

  1. INSERM, U1099, Rennes, 35000, France

    Oscar Acosta, Gael Drean, Antoine Simon, Renaud de Crevoisier & Pascal Haigron

  2. Université de Rennes 1, LTSI, Rennes, 35000, France

    Oscar Acosta, Gael Drean, Antoine Simon, Renaud de Crevoisier & Pascal Haigron

  3. The Australian e-Health Research Center-CSIRO, Brisbane, Australia

    Jason Dowling

  4. Département de Radiothérapie, Centre Eugène Marquis, Rennes, 35000, France

    Renaud de Crevoisier

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  1. Oscar Acosta
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  2. Jason Dowling
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  3. Gael Drean
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  4. Antoine Simon
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  5. Renaud de Crevoisier
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Correspondence to Oscar Acosta .

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Editors and Affiliations

  1. Department of Bioengineering, University of Louisville, Louisville, Kentucky, USA

    Ayman S. El-Baz

  2. University of Cagliari, Cagliari, Italy

    Luca Saba

  3. Biomedical Technologies, Inc Idaho State University (Affiliated), Roseville, California, USA

    Jasjit Suri

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Acosta, O., Dowling, J., Drean, G., Simon, A., de Crevoisier, R., Haigron, P. (2014). Multi-Atlas-Based Segmentation of Pelvic Structures from CT Scans for Planning in Prostate Cancer Radiotherapy. In: El-Baz, A., Saba, L., Suri, J. (eds) Abdomen and Thoracic Imaging. Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-8498-1_24

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  • DOI: https://doi.org/10.1007/978-1-4614-8498-1_24

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