Automatic tissue segmentation of neonate brain MR Images with subject-specific atlases

Marie Cherel, Francois Budin, Marcel Prastawa, Guido Gerig, Kevin Lee, Claudia Buss, Amanda Lyall, Kirsten Zaldarriaga Consing, Martin Styner

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Automatic tissue segmentation of the neonate brain using Magnetic Resonance Images (MRI) is extremely important to study brain development and perform early diagnostics but is challenging due to high variability and inhomogeneity in contrast throughout the image due to incomplete myelination of the white matter tracts. For these reasons, current methods often totally fail or give unsatisfying results. Furthermore, most of the subcortical midbrain structures are misclassified due to a lack of contrast in these regions. We have developed a novel method that creates a probabilistic subject-specific atlas based on a population atlas currently containing a number of manually segmented cases. The generated subject-specific atlas is sharp and adapted to the subject that is being processed. We then segment brain tissue classes using the newly created atlas with a single-atlas expectation maximization based method. Our proposed method leads to a much lower failure rate in our experiments. The overall segmentation results are considerably improved when compared to using a non-subject-specific, population average atlas. Additionally, we have incorporated diffusion information obtained from Diffusion Tensor Images (DTI) to improve the detection of white matter that is not visible at this early age in structural MRI (sMRI) due to a lack of myelination. Although this necessitates the acquisition of an additional sequence, the diffusion information improves the white matter segmentation throughout the brain, especially for the mid-brain structures such as the corpus callosum and the internal capsule.

    Original languageEnglish (US)
    Title of host publicationMedical Imaging 2015
    Subtitle of host publicationImage Processing
    EditorsMartin A. Styner, Sebastien Ourselin
    PublisherSPIE
    ISBN (Electronic)9781628415032
    DOIs
    StatePublished - 2015
    EventMedical Imaging 2015: Image Processing - Orlando, United States
    Duration: Feb 24 2015Feb 26 2015

    Publication series

    NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
    Volume9413
    ISSN (Print)1605-7422

    Other

    OtherMedical Imaging 2015: Image Processing
    CountryUnited States
    CityOrlando
    Period2/24/152/26/15

    Keywords

    • MRI
    • atlas
    • automatic
    • neonate
    • population
    • segmentation
    • subject-specific
    • tissue

    ASJC Scopus subject areas

    • Electronic, Optical and Magnetic Materials
    • Biomaterials
    • Atomic and Molecular Physics, and Optics
    • Radiology Nuclear Medicine and imaging

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  • Cite this

    Cherel, M., Budin, F., Prastawa, M., Gerig, G., Lee, K., Buss, C., Lyall, A., Zaldarriaga Consing, K., & Styner, M. (2015). Automatic tissue segmentation of neonate brain MR Images with subject-specific atlases. In M. A. Styner, & S. Ourselin (Eds.), Medical Imaging 2015: Image Processing [941311] (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 9413). SPIE. https://doi.org/10.1117/12.2082209