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International Workshop on Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries

BrainLes 2016: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries pp 206–216Cite as

Brain Tumor Segmentation by Variability Characterization of Tumor Boundaries

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10154))

Abstract

Automated medical image analysis can play an important role in diagnoses and treatment assessment, but integration and interpretation across heterogeneous data sources remain significant challenges. In particular, automated estimation of tumor extent in glioblastoma patients has been challenging given the diversity of tumor shapes and appearance characteristics due to differences in magnetic resonance (MR) imaging acquisition parameters, scanner variations and heterogeneity in tumor biology. With this work, we present an approach for automated tumor segmentation using multimodal MR images. The algorithm considers the variability arising from the intrinsic tumor heterogeneity and segmentation error to derive the tumor boundary and produce an estimate of segmentation error. Using the MICCAI 2015 dataset, a Dice coefficient of 0.74 was obtained for whole tumor, 0.55 for tumor core, and 0.54 for active tumor, achieving above average performance in comparison to other approaches evaluated on the BRATS benchmark.

Funded by the National Institutes of Health (NIH) under the award number R01CA1575533.

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Author information

Authors and Affiliations

  1. Medical Imaging Informatics Group, Department of Radiological Sciences, University of California, Los Angeles, USA

    Edgar A. Rios Piedra, Ricky K. Taira, Suzie El-Saden, Alex A. T. Bui & William Hsu

  2. Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, USA

    Edgar A. Rios Piedra, Benjamin M. Ellingson, Ricky K. Taira, Suzie El-Saden, Alex A. T. Bui & William Hsu

  3. Department of Bioengineering, University of California, Los Angeles, USA

    Edgar A. Rios Piedra, Benjamin M. Ellingson, Ricky K. Taira, Suzie El-Saden, Alex A. T. Bui & William Hsu

Authors
  1. Edgar A. Rios Piedra
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  2. Benjamin M. Ellingson
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  3. Ricky K. Taira
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  4. Suzie El-Saden
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  5. Alex A. T. Bui
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  6. William Hsu
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Corresponding author

Correspondence to Edgar A. Rios Piedra .

Editor information

Editors and Affiliations

  1. University of Zurich, Istituto Italiano di Tecnologia, Genoa, Italy

    Alessandro Crimi

  2. TU München, Computer Science, Munich, Germany

    Bjoern Menze

  3. Medical Informatics, University of Lübeck, Lübeck, Germany

    Oskar Maier

  4. Surgical Technology and Biomechanics, Universität Bern, Bern, Switzerland

    Mauricio Reyes

  5. Department of Medicine, University of Cambridge, Cambridge, United Kingdom

    Stefan Winzeck

  6. Institute of Medical Informatics, University of Lübeck, Lübeck, Germany

    Heinz Handels

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© 2016 Springer International Publishing AG

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Rios Piedra, E.A., Ellingson, B.M., Taira, R.K., El-Saden, S., Bui, A.A.T., Hsu, W. (2016). Brain Tumor Segmentation by Variability Characterization of Tumor Boundaries. In: Crimi, A., Menze, B., Maier, O., Reyes, M., Winzeck, S., Handels, H. (eds) Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. BrainLes 2016. Lecture Notes in Computer Science(), vol 10154. Springer, Cham. https://doi.org/10.1007/978-3-319-55524-9_20

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  • DOI: https://doi.org/10.1007/978-3-319-55524-9_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-55523-2

  • Online ISBN: 978-3-319-55524-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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