• DocumentCode
    146868
  • Title

    Automatic segmentation of neonatal brain magnetic resonance images

  • Author

    Devi, Chelli N. ; Chandrasekharan, Anupama ; Sundararaman, V.K. ; Alex, Zachariah C.

  • Author_Institution
    Vellore Inst. of Technol., Vellore, India
  • fYear
    2014
  • fDate
    3-5 April 2014
  • Firstpage
    640
  • Lastpage
    643
  • Abstract
    This paper provides an overview of magnetic resonance imaging of the neonatal brain, presents the challenges involved in segmenting the neonatal brain images and reviews the existing techniques for automatic segmentation, including atlas-based probabilistic segmentations and morphology based brain segmentation. It compares the various methods in practice and highlights their limitations, particularly the inadequacies in segmenting the myelinated portions of the brain. It also proposes a new approach to overcome these shortcomings.
  • Keywords
    biomedical MRI; brain; image segmentation; medical image processing; neurophysiology; paediatrics; probability; atlas-based probabilistic segmentations; automatic segmentation; morphology-based brain segmentation; myelinated portions; neonatal brain image segmentation; neonatal brain magnetic resonance images; Brain modeling; Image segmentation; Indexes; Magnetic resonance imaging; Manuals; Pathology; Pediatrics; Automatic segmentation; Brain atlas; Myelination; Neonatal brain magnetic resonance images;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications and Signal Processing (ICCSP), 2014 International Conference on
  • Conference_Location
    Melmaruvathur
  • Print_ISBN
    978-1-4799-3357-0
  • Type

    conf

  • DOI
    10.1109/ICCSP.2014.6949920
  • Filename
    6949920