An Advanced Data Structure for Large Medical Datasets

Information

• Publication Type: Master Thesis
• Workgroup(s)/Project(s):
  • Visualization Group
• Date: 2005
• TU Wien Library:
• First Supervisor:
  • Joy
  • Sören Grimm
  • Eduard Gröller

Abstract

The size of volumetric data acquired from computed tomography scanning devices is steadily increasing, which often makes it impractical to store the whole data in physical memory. Therefore, e±cient data structures are re- quired. In this thesis several data structures are examined in respect to application for computed tomography-angiography. In particular, memory consumption and performance of visualization are addressed. Additionally, a data structure based on adaptive meshes is implemented. This data struc- ture can leverage resources where they are needed. In order to generate the adaptive meshes, two di®erent algorithms are explained and compared to each other. The most common visualization techniques for angiography are described.

Additional Files and Images

Weblinks

No further information available.

BibTeX

@mastersthesis{hartmann-2005-adv,
  title =      "An Advanced Data Structure for Large Medical Datasets",
  author =     "Alexander Hartmann",
  year =       "2005",
  abstract =   "The size of volumetric data acquired from computed
               tomography scanning devices is steadily increasing, which
               often makes it impractical to store the whole data in
               physical memory. Therefore, e±cient data structures are re-
               quired. In this thesis several data structures are examined
               in respect to application for computed
               tomography-angiography. In particular, memory consumption
               and performance of visualization are addressed.
               Additionally, a data structure based on adaptive meshes is
               implemented. This data struc- ture can leverage resources
               where they are needed. In order to generate the adaptive
               meshes, two di®erent algorithms are explained and compared
               to each other. The most common visualization techniques for
               angiography are described.",
  address =    "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria",
  school =     "Institute of Computer Graphics and Algorithms, Vienna
               University of Technology ",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2005/hartmann-2005-adv/",
}