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Fully Automatic 3D Glioma Extraction in Multi-contrast MRI

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Image Analysis and Recognition (ICIAR 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8815))

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Abstract

This work deals with the fully automatic extraction of a glioma, the most common type of brain tumor, in multi-contrast 3D magnetic resonance volumes. The detection is based on the locating the area that breaks the left-right symmetry of the brain. The proposed method uses multi-contrast MRI, where FLAIR and T2-weighted volumes are employed. The algorithm was designed to extract the whole pathology as one region.

The created algorithm was tested on 80 volumes from publicly available BRATS databases containing multi-contrast 3D brain volumes afflicted by a brain tumor. These pathological structures had various sizes and shapes and were located in various parts of the brain. The extraction process was evaluated by Dice Coefficient(0.75). The proposed algorithm detected and extracted multifocal tumors as separated regions as well.

This work was supported by SIX CZ.1.05/2.1.00/03.0072, GACR 102/12/1104 and COST CZ LD14091.

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Authors and Affiliations

  1. Department of Telecommunications, Faculty of Electrical Engineering and Communication, Brno University of Technology, Technicka 12, 612 00, Brno, Czech Republic

    Pavel Dvorak

  2. Institute of Scientific Instruments of the ASCR, v.v.i., Kralovopolska 147, 612 64, Brno, Czech Republic

    Pavel Dvorak & Karel Bartusek

Authors
  1. Pavel Dvorak
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  2. Karel Bartusek
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Corresponding author

Correspondence to Pavel Dvorak .

Editor information

Editors and Affiliations

  1. Faculty of Engineering, University of Porto, Porto, Portugal

    Aurélio Campilho

  2. Dept. of Electrical and Computer Eng., University of Waterloo, Waterloo, Ontario, Canada

    Mohamed Kamel

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Dvorak, P., Bartusek, K. (2014). Fully Automatic 3D Glioma Extraction in Multi-contrast MRI. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2014. Lecture Notes in Computer Science(), vol 8815. Springer, Cham. https://doi.org/10.1007/978-3-319-11755-3_27

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  • DOI: https://doi.org/10.1007/978-3-319-11755-3_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11754-6

  • Online ISBN: 978-3-319-11755-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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