• DocumentCode
    617309
  • Title

    Multi-Tensor Field spectral segmentation for white matter fiber bundle classification

  • Author

    Ocegueda, Omar ; Rivera, Marco

  • Author_Institution
    Centro de Investig. en Mat. Guanajuato, Guanajuato, Mexico
  • fYear
    2013
  • fDate
    7-11 April 2013
  • Firstpage
    262
  • Lastpage
    265
  • Abstract
    We present an algorithm for segmenting the white-matter axon fiber bundles from HARDI images. We formulate the segmentation problem as a Multi-Tensor Field segmentation problem in which the compartments of each Multi-Tensor may belong to different classes, allowing the algorithm to handle crossing fiber tracts. Experimental results on two publicly available synthetic datasets and the fiber-cup phantom show that fiber crossings can be effectively separated by using this approach, and preliminary results on real data show that the segmentation obtained is consistent with known anatomical structures.
  • Keywords
    biodiffusion; biomedical MRI; brain; image classification; image segmentation; medical image processing; phantoms; tensors; HARDI image; anatomical structure; fiber tract; fiber-cup phantom; multitensor field spectral segmentation; real data; synthetic dataset; white matter axon fiber bundle classification; Image segmentation; Magnetic resonance imaging; Nerve fibers; Phantoms; Tensile stress; Vectors; Brain imaging; Image segmentation; Tensor and vector field analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Imaging (ISBI), 2013 IEEE 10th International Symposium on
  • Conference_Location
    San Francisco, CA
  • ISSN
    1945-7928
  • Print_ISBN
    978-1-4673-6456-0
  • Type

    conf

  • DOI
    10.1109/ISBI.2013.6556462
  • Filename
    6556462