• DocumentCode
    2463991
  • Title

    Locally-Constrained Region-Based Methods for DW-MRI Segmentation

  • Author

    Melonakos, John ; Niethammer, Marc ; Mohan, Vandana ; Kubicki, Marek ; Miller, James V. ; Tannenbaum, Allen

  • Author_Institution
    Georgia Inst. of Technol., Atlanta
  • fYear
    2007
  • fDate
    14-21 Oct. 2007
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    In this paper, we describe a method for segmenting fiber bundles from diffusion-weighted magnetic resonance images using a locally-constrained region based approach. From a pre-computed optimal path, the algorithm propagates outward capturing only those voxels which are locally connected to the fiber bundle. Rather than attempting to find large numbers of open curves or single fibers, which individually have questionable meaning, this method segments the full fiber bundle region. The strengths of this approach include its ease-of-use, computational speed, and applicability to a wide range of fiber bundles. In this work, we show results for segmenting the cingulum bundle. Finally, we explain how this approach and extensions thereto overcome a major problem that typical region-based flows experience when attempting to segment neural fiber bundles.
  • Keywords
    biomedical MRI; brain; image segmentation; medical image processing; DW-MRI segmentation; diffusion-weighted magnetic resonance image; locally-constrained region based approach; neural fiber bundle; Bayesian methods; Biomedical computing; Biomedical imaging; Decision making; Hospitals; Image segmentation; Magnetic resonance; Signal to noise ratio; Stochastic resonance; Tensile stress;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on
  • Conference_Location
    Rio de Janeiro
  • ISSN
    1550-5499
  • Print_ISBN
    978-1-4244-1630-1
  • Electronic_ISBN
    1550-5499
  • Type

    conf

  • DOI
    10.1109/ICCV.2007.4409167
  • Filename
    4409167