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    Automated segmentation of the substantia nigra, subthalamic nucleus and red nucleus in 7T data at young and old age.

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    Author
    Visser, E; Keuken, MC; Forstmann, BU; Jenkinson, M
    Date
    2016-10-01
    Source Title
    NeuroImage
    Publisher
    Elsevier BV
    University of Melbourne Author/s
    Jenkinson, Mark
    Affiliation
    Centre for Neuroscience
    Metadata
    Show full item record
    Document Type
    Journal Article
    Citations
    Visser, E., Keuken, M. C., Forstmann, B. U. & Jenkinson, M. (2016). Automated segmentation of the substantia nigra, subthalamic nucleus and red nucleus in 7T data at young and old age.. Neuroimage, 139, pp.324-336. https://doi.org/10.1016/j.neuroimage.2016.06.039.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/256305
    DOI
    10.1016/j.neuroimage.2016.06.039
    Open Access at PMC
    http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4988791
    Abstract
    With recent developments in MR acquisition at 7T, smaller brainstem structures such as the red nuclei, substantia nigra and subthalamic nuclei can be imaged with good contrast and resolution. These structures have important roles both in the study of the healthy brain and in diseases such as Parkinson's disease, but few methods have been described to automatically segment them. In this paper, we extend a method that we have previously proposed for segmentation of the striatum and globus pallidus to segment these deeper and smaller structures. We modify the method to allow more direct control over segmentation smoothness by using a Markov random field prior. We investigate segmentation performance in three age groups and show that the method produces consistent results that correspond well with manual segmentations. We perform a vertex-based analysis to identify changes with age in the shape of the structures and present results suggesting that the method may be at least as effective as manual delineation in capturing differences between subjects.

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