Incorporating Parameter Uncertainty in Bayesian Segmentation Models: Application to Hippocampal Subfield Volumetry

J. E. Iglesias, M. R. Sabuncu, Koen Van Leemput

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    Abstract

    Many successful segmentation algorithms are based on Bayesian models in which prior anatomical knowledge is combined with the available image information. However, these methods typically have many free parameters that are estimated to obtain point estimates only, whereas a faithful Bayesian analysis would also consider all possible alternate values these parameters may take. In this paper, we propose to incorporate the uncertainty of the free parameters in Bayesian segmentation models more accurately by using Monte Carlo sampling. We demonstrate our technique by sampling atlas warps in a recent method for hippocampal subfield segmentation, and show a significant improvement in an Alzheimer’s disease classification task. As an additional benefit, the method also yields informative “error bars” on the segmentation results for each of the individual sub-structures.
    Original languageEnglish
    Title of host publicationMedical Image Computing and Computer-Assisted Intervention – MICCAI 2012 : 15th International Conference, Nice, France, October 1-5, 2012, Proceedings, Part III
    PublisherSpringer
    Publication date2012
    Pages50-57
    ISBN (Print)978-3-642-33453-5
    ISBN (Electronic)978-3-642-33454-2
    DOIs
    Publication statusPublished - 2012
    Event15th International Conference on Medical Image Computing and Computer Assisted Intervention - Nice, France
    Duration: 1 Oct 20125 Oct 2012
    http://www.miccai2012.org/

    Conference

    Conference15th International Conference on Medical Image Computing and Computer Assisted Intervention
    CountryFrance
    CityNice
    Period01/10/201205/10/2012
    Internet address
    SeriesLecture Notes in Computer Science
    Volume7512
    ISSN0302-9743

    Cite this

    Iglesias, J. E., Sabuncu, M. R., & Van Leemput, K. (2012). Incorporating Parameter Uncertainty in Bayesian Segmentation Models: Application to Hippocampal Subfield Volumetry. In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012: 15th International Conference, Nice, France, October 1-5, 2012, Proceedings, Part III (pp. 50-57). Springer. Lecture Notes in Computer Science, Vol.. 7512 https://doi.org/10.1007/978-3-642-33454-2_7