• DocumentCode
    3252919
  • Title

    3D brain tissue selection and segmentation from MRI

  • Author

    Uher, Vaclav ; Burget, Radim ; Masek, Jaroslav ; Dutta, Malay Kishore

  • Author_Institution
    Dept. of Telecommun., Brno Univ. of Technol., Brno, Czech Republic
  • fYear
    2013
  • fDate
    2-4 July 2013
  • Firstpage
    839
  • Lastpage
    842
  • Abstract
    Magnetic resonance imaging (MRI) is a visualizing method used in radiology that enables viewing internal structures of the body. Using several mathematical methods with data retrieved from MRI it is possible to quantify the brain compartment volume, which has many applications in cognitive, clinical and comparative neurosciences. This paper introduces a new fully automatic method, which can measure the volume of brain tissue using scans obtained from MRI devices. The method introduced in this paper was trained on data taken from 12 patients and the trained result was validated on other independent data obtained from 10 patients and compared to a human expert´s accuracy. The result achieves 99.407 % +/- 0.062 voxel error accuracy, which is comparable to results achieved by humans (99.540 % + 0.0775) but in a significantly shorter time and without the need of human involvement.
  • Keywords
    biological tissues; biomedical MRI; brain; image segmentation; medical image processing; volume measurement; 3D brain compartment volume quantification; 3D brain tissue segmentation; 3D brain tissue selection; MRI device; body internal structure visualization; brain tissue volume measurement; clinical neuroscience; cognitive neuroscience; comparative neuroscience; data retrieval; magnetic resonance imaging; mathematical method; radiology; voxel error accuracy; Accuracy; Brain modeling; Image segmentation; Magnetic resonance imaging; Testing; Three-dimensional displays; Image processing; brain selection; machine learning; segmentation; skull stripping;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Telecommunications and Signal Processing (TSP), 2013 36th International Conference on
  • Conference_Location
    Rome
  • Print_ISBN
    978-1-4799-0402-0
  • Type

    conf

  • DOI
    10.1109/TSP.2013.6614057
  • Filename
    6614057