Spatio-temporal segmentation of active multiple sclerosis lesions in serial MRI data

Daniel Welti, Guido Gerig, Ernst Wilhelm Radü, Ludwig Kappos, Gabor Székely

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

    Abstract

    This paper presents a new approach for the automatic segmentation and characterization of active MS lesions in 4D data of multiple sequences. Traditional segmentation of 4D data applies individual 3D spatial segmentation to each image data set, thus not making use of correlation over time. More recently, a time series analysis has been applied to 4D data to reveal active lesions [3]. However, misregistration at tissue borders led to false positive lesion voxels. Lesion development is a complex spatio-temporal process, consequently methods concentrating exclusively on the spatial or temporal aspects of it cannot be expected to provide optimal results. Active MS lesions were extracted from the 4D data in order to quantify MR-based spatiotemporal changes in the brain. A spatio-temporal lesion model generated by principal component analysis allowed robust identification of active MS lesions overcoming the drawbacks of traditional purely spatial or purely temporal segmentation methods.

    Original languageEnglish (US)
    Title of host publicationInformation Processing in Medical Imaging - 17th International Conference, IPMI 2001, Proceedings
    EditorsRichard M. Leahy, Michael F. Insana
    PublisherSpringer Verlag
    Pages438-445
    Number of pages8
    ISBN (Electronic)3540422455, 9783540422457
    StatePublished - Jan 1 2001
    Event17th International Conference on Information Processing in Medical Imaging, IPMI 2001 - Davis, United States
    Duration: Jun 18 2001Jun 22 2001

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume2082
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Other

    Other17th International Conference on Information Processing in Medical Imaging, IPMI 2001
    CountryUnited States
    CityDavis
    Period6/18/016/22/01

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    ASJC Scopus subject areas

    • Theoretical Computer Science
    • Computer Science(all)

    Cite this

    Welti, D., Gerig, G., Radü, E. W., Kappos, L., & Székely, G. (2001). Spatio-temporal segmentation of active multiple sclerosis lesions in serial MRI data. In R. M. Leahy, & M. F. Insana (Eds.), Information Processing in Medical Imaging - 17th International Conference, IPMI 2001, Proceedings (pp. 438-445). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2082). Springer Verlag.