Diffeomorphic shape trajectories for improved longitudinal segmentation and statistics

Prasanna Muralidharan, James Fishbaugh, Hans J. Johnson, Stanley Durrleman, Jane S. Paulsen, Guido Gerig, P. Thomas Fletcher

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

    Abstract

    Longitudinal imaging studies involve tracking changes in individuals by repeated image acquisition over time. The goal of these studies is to quantify biological shape variability within and across individuals, and also to distinguish between normal and disease populations. However, data variability is influenced by outside sources such as image acquisition, image calibration, human expert judgment, and limited robustness of segmentation and registration algorithms. In this paper, we propose a two-stage method for the statistical analysis of longitudinal shape. In the first stage, we estimate diffeomorphic shape trajectories for each individual that minimize inconsistencies in segmented shapes across time. This is followed by a longitudinal mixed-effects statistical model in the second stage for testing differences in shape trajectories between groups. We apply our method to a longitudinal database from PREDICT-HD and demonstrate our approach reduces unwanted variability for both shape and derived measures, such as volume. This leads to greater statistical power to distinguish differences in shape trajectory between healthy subjects and subjects with a genetic biomarker for Huntington's disease (HD).

    Original languageEnglish (US)
    Title of host publicationMedical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - 17th International Conference, Proceedings
    PublisherSpringer Verlag
    Pages49-56
    Number of pages8
    Volume8675 LNCS
    EditionPART 3
    ISBN (Print)9783319104423
    DOIs
    StatePublished - 2014
    Event17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - Boston, MA, United States
    Duration: Sep 14 2014Sep 18 2014

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    NumberPART 3
    Volume8675 LNCS
    ISSN (Print)03029743
    ISSN (Electronic)16113349

    Other

    Other17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014
    CountryUnited States
    CityBoston, MA
    Period9/14/149/18/14

    Fingerprint

    Segmentation
    Image acquisition
    Trajectories
    Statistics
    Trajectory
    Biomarkers
    Image Acquisition
    Statistical methods
    Calibration
    Imaging techniques
    Expert Judgment
    Mixed Effects
    Testing
    Statistical Power
    Inconsistency
    Registration
    Statistical Model
    Statistical Analysis
    Quantify
    Imaging

    ASJC Scopus subject areas

    • Computer Science(all)
    • Theoretical Computer Science

    Cite this

    Muralidharan, P., Fishbaugh, J., Johnson, H. J., Durrleman, S., Paulsen, J. S., Gerig, G., & Fletcher, P. T. (2014). Diffeomorphic shape trajectories for improved longitudinal segmentation and statistics. In Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - 17th International Conference, Proceedings (PART 3 ed., Vol. 8675 LNCS, pp. 49-56). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8675 LNCS, No. PART 3). Springer Verlag. https://doi.org/10.1007/978-3-319-10443-0_7

    Diffeomorphic shape trajectories for improved longitudinal segmentation and statistics. / Muralidharan, Prasanna; Fishbaugh, James; Johnson, Hans J.; Durrleman, Stanley; Paulsen, Jane S.; Gerig, Guido; Fletcher, P. Thomas.

    Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - 17th International Conference, Proceedings. Vol. 8675 LNCS PART 3. ed. Springer Verlag, 2014. p. 49-56 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8675 LNCS, No. PART 3).

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

    Muralidharan, P, Fishbaugh, J, Johnson, HJ, Durrleman, S, Paulsen, JS, Gerig, G & Fletcher, PT 2014, Diffeomorphic shape trajectories for improved longitudinal segmentation and statistics. in Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - 17th International Conference, Proceedings. PART 3 edn, vol. 8675 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 3, vol. 8675 LNCS, Springer Verlag, pp. 49-56, 17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014, Boston, MA, United States, 9/14/14. https://doi.org/10.1007/978-3-319-10443-0_7
    Muralidharan P, Fishbaugh J, Johnson HJ, Durrleman S, Paulsen JS, Gerig G et al. Diffeomorphic shape trajectories for improved longitudinal segmentation and statistics. In Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - 17th International Conference, Proceedings. PART 3 ed. Vol. 8675 LNCS. Springer Verlag. 2014. p. 49-56. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 3). https://doi.org/10.1007/978-3-319-10443-0_7
    Muralidharan, Prasanna ; Fishbaugh, James ; Johnson, Hans J. ; Durrleman, Stanley ; Paulsen, Jane S. ; Gerig, Guido ; Fletcher, P. Thomas. / Diffeomorphic shape trajectories for improved longitudinal segmentation and statistics. Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - 17th International Conference, Proceedings. Vol. 8675 LNCS PART 3. ed. Springer Verlag, 2014. pp. 49-56 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 3).
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    AU - Paulsen, Jane S.

    AU - Gerig, Guido

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