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Interactive Visualization of Particle-In-Cell Simulations
Linköping University, Department of Science and Technology, Visual Information Technology and Applications (VITA). Linköping University, The Institute of Technology.ORCID iD: 0000-0002-9288-5322
Linköping University, Department of Science and Technology, Visual Information Technology and Applications (VITA). Linköping University, The Institute of Technology.ORCID iD: 0000-0003-4055-0552
Linköping University, Department of Science and Technology, Visual Information Technology and Applications (VITA). Linköping University, The Institute of Technology.ORCID iD: 0000-0002-9466-9826
2000 (English)In: Proceedings of IEEE Visualization 2000, Salt Lake City, USA, 2000, 469-472 p.Conference paper, Published paper (Other academic)
Place, publisher, year, edition, pages
2000. 469-472 p.
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-13942OAI: oai:DiVA.org:liu-13942DiVA: diva2:22272
Available from: 2006-09-14 Created: 2006-09-14 Last updated: 2017-11-03
In thesis
1. Efficient Methods for Direct Volume Rendering of Large Data Sets
Open this publication in new window or tab >>Efficient Methods for Direct Volume Rendering of Large Data Sets
2006 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Direct Volume Rendering (DVR) is a technique for creating images directly from a representation of a function defined over a three-dimensional domain. The technique has many application fields, such as scientific visualization and medical imaging. A striking property of the data sets produced within these fields is their ever increasing size and complexity. Despite the advancements of computing resources these data sets seem to grow at even faster rates causing severe bottlenecks in terms of data transfer bandwidths, memory capacity and processing requirements in the rendering pipeline.

This thesis focuses on efficient methods for DVR of large data sets. At the core of the work lies a level-of-detail scheme that reduces the amount of data to process and handle, while optimizing the level-of-detail selection so that high visual quality is maintained. A set of techniques for domain knowledge encoding which significantly improves assessment and prediction of visual significance for blocks in a volume are introduced. A complete pipeline for DVR is presented that uses the data reduction achieved by the level-of-detail selection to minimize the data requirements in all stages. This leads to reduction of disk I/O as well as host and graphics memory. The data reduction is also exploited to improve the rendering performance in graphics hardware, employing adaptive sampling both within the volume and within the rendered image.

The developed techniques have been applied in particular to medical visualization of large data sets on commodity desktop computers using consumer graphics processors. The specific application of virtual autopsies has received much interest, and several developed data classification schemes and rendering techniques have been motivated by this application. The results are, however, general and applicable in many fields and significant performance and quality improvements over previous techniques are shown.

Place, publisher, year, edition, pages
Institutionen för teknik och naturvetenskap, 2006
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1043
Keyword
Computer Graphics, Scientific Visualization, Medical Imaging, Volume Rendering, Raycasting, Transfer Functions, Level-of-detail, Fuzzy Classification, Virtual Autopsies
National Category
Computer Science
Identifiers
urn:nbn:se:liu:diva-7232 (URN)91-85523-05-4 (ISBN)
Public defence
2006-10-06, K3, Kåkenhus, Campus Norrköping, Linköpings universitet, Norrköping, 09:15 (English)
Opponent
Supervisors
Note
On the defence date the status of article IX was Accepted.Available from: 2006-09-14 Created: 2006-09-14 Last updated: 2015-09-22

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Ljung, PatricDieckmann, Mark EYnnerman, Anders

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CiteExportLink to record
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Citation style
  • apa
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