Automatic segmentation of neonatal brain MRI

Marcel Prastawa, John Gilmore, Weili Lin, Guido Gerig

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

    Abstract

    This paper describes an automatic tissue segmentation method for neonatal MRI. The analysis and study of neonatal brain MRI is of great interest due to its potential for studying early growth patterns and morphologic change in neurodevelopmental disorders. Automatic segmentation of these images is a challenging task mainly due to the low intensity contrast and the non-uniformity of white matter intensities, where white matter can be divided into early myelination regions and non-myelinated regions. The degree of myelination is a fractional voxel property that represents regional changes of white matter as a function of age. Our method makes use of a registered probabilistic brain atlas to select training samples and to be used as a spatial prior. The method first uses graph clustering and robust estimation to estimate the initial intensity distributions. The estimates are then used together with the spatial priors to perform bias correction. Finally, the method refines the segmentation using sample pruning and non-parametric density estimation. Preliminary results show that the method is able to segment the major brain structures, identifying early myelination regions and non-myelinated regions.

    Original languageEnglish (US)
    Title of host publicationLecture Notes in Computer Science
    EditorsC. Barillot, D.R. Haynor, P. Hellier
    Pages10-17
    Number of pages8
    Volume3216
    EditionPART 1
    StatePublished - 2004
    EventMedical Image Computing and Computer-Assisted Intervention, MICCAI 2004 - 7th International Conference, Proceedings - Saint-Malo, France
    Duration: Sep 26 2004Sep 29 2004

    Other

    OtherMedical Image Computing and Computer-Assisted Intervention, MICCAI 2004 - 7th International Conference, Proceedings
    CountryFrance
    CitySaint-Malo
    Period9/26/049/29/04

    ASJC Scopus subject areas

    • Computer Science (miscellaneous)
    • Computer Science(all)
    • Theoretical Computer Science

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  • Cite this

    Prastawa, M., Gilmore, J., Lin, W., & Gerig, G. (2004). Automatic segmentation of neonatal brain MRI. In C. Barillot, D. R. Haynor, & P. Hellier (Eds.), Lecture Notes in Computer Science (PART 1 ed., Vol. 3216, pp. 10-17)