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    Improving Visualisation of Large Multi-Variate Datasets: New Hardware-Based Compression Algorithms and Rendering Techniques

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    Author
    Chernoglazov, Alexander Igorevich
    Date
    2012
    Permanent Link
    http://hdl.handle.net/10092/7004
    Thesis Discipline
    Computer Science
    Degree Grantor
    University of Canterbury
    Degree Level
    Masters
    Degree Name
    Master of Science

    Spectral computed tomography (CT) is a novel medical imaging technique that involves simultaneously counting photons at several energy levels of the x-ray spectrum to obtain a single multi-variate dataset. Visualisation of such data poses significant challenges due its extremely large size and the need for interactive performance for scientific and medical end-users. This thesis explores the properties of spectral CT datasets and presents two algorithms for GPU-accelerated real-time rendering from compressed spectral CT data formats. In addition, we describe an optimised implementation of a volume raycasting algorithm on modern GPU hardware, tailored to the visualisation of spectral CT data.

    Subjects
    visualisation
     
    compression
     
    volume rendering
     
    gpu
     
    gpgpu
     
    cuda
     
    spectral ct
     
    ct
     
    rendering
     
    optimisation
    Collections
    • Engineering: Theses and Dissertations [2159]
    Rights
    http://library.canterbury.ac.nz/thesis/etheses_copyright.shtml

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