Task based visualization of 5D brain EIT data

Yan Zhang, Peter J. Passmore , Richard H. Bayford

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


    Visualization is vital for medical research and clinical applications to interpret information presented in medical imaging data. EIT (Electrical Impedance Tomography) is a recently developed medical imaging technique, which is able to collect 5D spectral-temporal-spatial data. Visualization of multi-dimensional medical imaging data is still a challenge. Making use of the TMDV (Task-based Multi-Dimensional Visualization) method and CTE (Cubic Task Explore) model, a task based prototype system, EIT5DVis, is developed for the visualization of 5D brain EIT data in this paper. The evaluation result demonstrates the usability of EIT5DVis prototype visualization system and the effectiveness of the TMVD method and CTE model for the visualization of multi-dimensional medical imaging data.
    Original languageEnglish
    Title of host publicationSAC '09 Proceedings of the 2009 ACM symposium on Applied Computing
    Place of PublicationNew York
    PublisherAssociation for Computing Machinery (ACM)
    Number of pages5
    ISBN (Print)978-1-60558-166-8
    Publication statusPublished - 8 Mar 2009
    Event24th Annual ACM Symposium on Applied Computing - Hilton Hawaiian Village Beach Resort & Spa, Honolulu, United States
    Duration: 8 Mar 200912 Mar 2009
    https://www.sigapp.org/sac/sac2009/ (Link to conference website)


    Conference24th Annual ACM Symposium on Applied Computing
    Abbreviated titleSAC '09
    Country/TerritoryUnited States
    Internet address


    • visualization
    • task based
    • EIT image
    • multi-dimensional


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