Improving Visualisation of Large Multi-Variate Datasets: New Hardware-Based Compression Algorithms and Rendering Techniques
Author
Chernoglazov, Alexander Igorevich
Date
2012Permanent Link
http://hdl.handle.net/10092/7004Thesis Discipline
Computer ScienceDegree Grantor
University of CanterburyDegree Level
MastersDegree Name
Master of ScienceSpectral 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.