Longitudinal modeling of glaucoma progression using 2-dimensional continuous-time hidden Markov model

Yu Ying Liu, Hiroshi Ishikawa, Mei Chen, Gadi Wollstein, Joel S. Schuman, James M. Rehg

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

    Abstract

    We propose a 2D continuous-time Hidden Markov Model (2D CT-HMM) for glaucoma progression modeling given longitudinal structural and functional measurements. CT-HMM is suitable for modeling longitudinal medical data consisting of visits at arbitrary times, and 2D state structure is more appropriate for glaucoma since the time courses of functional and structural degeneration are usually different. The learned model not only corroborates the clinical findings that structural degeneration is more evident than functional degeneration in early glaucoma and the opposite is observed in more advanced stages, but also reveals the exact stages where the trend reverses. A method to detect time segments of fast progression is also proposed. Our results show that this detector can effectively identify patients with rapid degeneration. The model and the derived detector can be of clinical value for glaucoma monitoring.

    Original languageEnglish (US)
    Title of host publicationMedical Image Computing and Computer-Assisted Intervention, MICCAI 2013 - 16th International Conference, Proceedings
    Pages444-451
    Number of pages8
    EditionPART 2
    DOIs
    StatePublished - Oct 24 2013
    Event16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013 - Nagoya, Japan
    Duration: Sep 22 2013Sep 26 2013

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    NumberPART 2
    Volume8150 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013
    CountryJapan
    CityNagoya
    Period9/22/139/26/13

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    ASJC Scopus subject areas

    • Theoretical Computer Science
    • Computer Science(all)

    Cite this

    Liu, Y. Y., Ishikawa, H., Chen, M., Wollstein, G., Schuman, J. S., & Rehg, J. M. (2013). Longitudinal modeling of glaucoma progression using 2-dimensional continuous-time hidden Markov model. In Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013 - 16th International Conference, Proceedings (PART 2 ed., pp. 444-451). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8150 LNCS, No. PART 2). https://doi.org/10.1007/978-3-642-40763-5_55