liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Efficient Methods for Direct Volume Rendering of Large Data Sets
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
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 [en]
Computer Graphics, Scientific Visualization, Medical Imaging, Volume Rendering, Raycasting, Transfer Functions, Level-of-detail, Fuzzy Classification, Virtual Autopsies
National Category
Computer Science
Identifiers
URN: urn:nbn:se:liu:diva-7232ISBN: 91-85523-05-4 (print)OAI: oai:DiVA.org:liu-7232DiVA: diva2:22281
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
List of papers
1. Interactive Visualization of Particle-In-Cell Simulations
Open this publication in new window or tab >>Interactive Visualization of Particle-In-Cell Simulations
2000 (English)In: Proceedings of IEEE Visualization 2000, Salt Lake City, USA, 2000, 469-472 p.Conference paper, Published paper (Other academic)
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-13942 (URN)
Available from: 2006-09-14 Created: 2006-09-14 Last updated: 2017-11-03
2. Transfer Function Based Adaptive Decompresion for Volume Rendering of Large Medical Data Sets
Open this publication in new window or tab >>Transfer Function Based Adaptive Decompresion for Volume Rendering of Large Medical Data Sets
2004 (English)In: Proceedings of IEEE/ACM Symposium on Volume Visualization 2004, Austin, USA, IEEE , 2004, 25-32 p.Conference paper, Published paper (Refereed)
Abstract [en]

The size of standard volumetric data sets in medical imaging is rapidly increasing causing severe performance limitations in direct volume rendering pipelines. The methods presented in this paper exploit the medical knowledge embedded in the transfer function to reduce the required bandwidth in the pipeline. Typically, medical transfer functions cause large subsets of the volume to give little or no contribution to the rendered image. Thus, parts of the volume can be represented at low resolution while retaining overall visual quality. This paper introduces the use of transfer functions at decompression time to guide a level-of-detail selection scheme. The method may be used in combination with traditional lossy or lossless compression schemes. We base our current implementation on a multi-resolution data representation using compressed wavelet transformed blocks. The presented results using the adaptive decompression demonstrate a significant reduction in the required amount of data while maintaining rendering quality. Even though the focus of this paper is medical imaging, the results are applicable to volume rendering in many other domains.

Place, publisher, year, edition, pages
IEEE, 2004
Keyword
Adaptive decompression, Image quality measures, Medical imaging, Multiresolution, Transfer function, Volume compression, Volume rendering, Wavelet transform
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-13943 (URN)10.1109/SVVG.2004.14 (DOI)
Available from: 2006-09-14 Created: 2006-09-14 Last updated: 2015-09-22
3. Extending and Simplifying Transfer Function Design in Medical Volume Rendering Using Local Histograms
Open this publication in new window or tab >>Extending and Simplifying Transfer Function Design in Medical Volume Rendering Using Local Histograms
2005 (English)In: Proceedings EuroGraphics/IEEE Symposium on Visualization 2005, Leeds, UK, 2005, 263-270 p.Conference paper, Published paper (Other academic)
Abstract [en]

Direct Volume Rendering (DVR) is known to be of diagnostic value in the analysis of medical data sets. However, its deployment in everyday clinical use has so far been limited. Two major challenges are that the current methods for Transfer Function (TF) construction are too complex and that the tissue separation abilities of the TF need to be extended. In this paper we propose the use of histogram analysis in local neighborhoods to address both these conflicting problems. To reduce TF construction difficulty, we introduce Partial Range Histograms in an automatic tissue detection scheme, which in connection with Adaptive Trapezoids enable efficient TF design. To separate tissues with overlapping intensity ranges, we propose a fuzzy classification based on local histograms as a second TF dimension. This increases the power of the TF, while retaining intuitive presentation and interaction.

National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-13944 (URN)10.2312/VisSym/EuroVis05/263-270 (DOI)
Available from: 2006-09-14 Created: 2006-09-14 Last updated: 2015-09-22
4. Multiresolution Interblock Interpolation in Direct Volume Rendering
Open this publication in new window or tab >>Multiresolution Interblock Interpolation in Direct Volume Rendering
2006 (English)In: Proceedings of Eurographics/IEEE Symposium on Visualization 2006, Lisbon, Portugal, 2006, 259-266 p.Conference paper, Published paper (Other academic)
Abstract [en]

We present a direct interblock interpolation technique that enables direct volume rendering of blocked, multiresolution volumes. The proposed method smoothly interpolates between blocks of arbitrary block-wise level-of-detail (LOD) without sample replication or padding. This permits extreme changes in resolution across block boundaries and removes the interblock dependency for the LOD creation process. In addition the full data reduction from the LOD selection can be maintained throughout the rendering pipeline. Our rendering pipeline employs a flat block subdivision followed by a transfer function based adaptive LOD scheme. We demonstrate the effectiveness of our method by rendering volumes of the order of gigabytes using consumer graphics cards on desktop PC systems.

Keyword
Viewing algorithms; Image Processing; Computer Vision
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-13945 (URN)10.2312/VisSym/EuroVis06/259-266 (DOI)
Available from: 2006-09-14 Created: 2006-09-14 Last updated: 2015-09-22
5. The alpha-histogram: Using Spatial Coherence to Enhance Histograms and Transfer Function Design
Open this publication in new window or tab >>The alpha-histogram: Using Spatial Coherence to Enhance Histograms and Transfer Function Design
Show others...
2006 (English)In: Proceedings Eurographics/IEEE Symposium on Visualization 2006, Lisbon, Portugal, 2006, 227-234 p.Conference paper, Published paper (Other academic)
Abstract [en]

The high complexity of Transfer Function (TF) design is a major obstacle to widespread routine use of Direct Volume Rendering, particularly in the case of medical imaging. Both manual and automatic TF design schemes would benefit greatly from a fast and simple method for detection of tissue value ranges. To this end, we introduce the a-histogram, an enhancement that amplifies ranges corresponding to spatially coherent materials. The properties of the a-histogram have been explored for synthetic data sets and then successfully used to detect vessels in 20 Magnetic Resonance angiographies, proving the potential of this approach as a fast and simple technique for histogram enhancement in general and for TF construction in particular.

Keyword
Picture/Image Generation; Methodology and Techniques; Three-Dimensional Graphics and Realism
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-13946 (URN)10.2312/VisSym/EuroVis06/227-234 (DOI)
Available from: 2006-09-14 Created: 2006-09-14 Last updated: 2015-09-22
6. Adaptive Sampling in Single Pass, GPU-based Raycasting of Multiresolution Volumes
Open this publication in new window or tab >>Adaptive Sampling in Single Pass, GPU-based Raycasting of Multiresolution Volumes
2006 (English)In: Proceedings Eurographics/IEEE International Workshop on Volume Graphics 2006, Boston, USA, 2006, 39-46 p.Conference paper, Published paper (Other academic)
Abstract [en]

This paper presents a novel direct volume rendering technique for adaptive object- and image-space sampling density of multiresolution volumes. The raycasting is implemented entirely on the GPU in a single pass fragment program which adapts the sampling density along rays, guided by block resolutions. The multiresolution volumes are provided by a transfer function based level-of-detail scheme adaptively loading large out-of-core volumes. Adaptive image-space sampling is achieved by gathering projected basic volume block statistics for screen tiles and then allocating a level-of-detail for each tile. This combination of techniques provides a significant reduction of processing requirements while maintaining high quality rendering.

Keyword
Viewing algorithms; Image Processing; Computer Vision
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-13947 (URN)10.2312/VG/VG06/039-046 (DOI)
Available from: 2006-09-14 Created: 2006-09-14 Last updated: 2015-05-27
7. Multi-Dimensional Transfer Function Design Using Sorted Histograms
Open this publication in new window or tab >>Multi-Dimensional Transfer Function Design Using Sorted Histograms
2006 (English)In: Proceedings Eurographics/IEEE International Workshop on Volume Graphics 2006, Boston, USA, 2006, 1-8 p.Conference paper, Published paper (Other academic)
Abstract [en]

Multi-dimensional Transfer Functions (MDTFs) are increasingly used in volume rendering to produce high quality visualizations of complex data sets. A major factor limiting the use of MDTFs is that the available design tools have not been simple enough to reach wide usage outside of the research context, for instance in clinical medical imaging. In this paper we address this problem by defining an MDTF design concept based on improved histogram display and interaction in an exploratory process. To this end we propose sorted histograms, 2D histograms that retain the intuitive appearance of a traditional 1D histogram while conveying a second attribute. We deploy the histograms in medical visualizations using data attributes capturing domain knowledge e.g. in terms of homogeneity and typical surrounding of tissues. The resulting renderings demonstrate that the proposed concept supports a vast number of visualization possibilities based on multi-dimensional attribute data.

National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-13948 (URN)10.2312/VG/VG06/001-008 (DOI)
Available from: 2006-09-14 Created: 2006-09-14 Last updated: 2015-09-22
8. Local histograms for design of Transfer Functions in Direct Volume Rendering
Open this publication in new window or tab >>Local histograms for design of Transfer Functions in Direct Volume Rendering
2006 (English)In: IEEE Transactions on Visualization and Computer Graphics, ISSN 1077-2626, E-ISSN 1941-0506, Vol. 12, no 6, 1570-1579 p.Article in journal (Other academic) Published
Abstract [en]

Direct Volume Rendering (DVR) is of increasing diagnostic value in the analysis of data sets captured using the latest medical imaging modalities. The deployment of DVR in everyday clinical work, however, has so far been limited. One contributing factor is that current Transfer Function (TF) models can encode only a small fraction of the user's domain knowledge. In this paper, we use histograms of local neighborhoods to capture tissue characteristics. This allows domain knowledge on spatial relations in the data set to be integrated into the TF. As a first example, we introduce Partial Range Histograms in an automatic tissue detection scheme and present its effectiveness in a clinical evaluation. We then use local histogram analysis to perform a classification where the tissue-type certainty is treated as a second TF dimension. The result is an enhanced rendering where tissues with overlapping intensity ranges can be discerned without requiring the user to explicitly define a complex, multidimensional TF.

Keyword
Volume visualization, transfer function, medical imaging, classification, partial range histogram
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-13949 (URN)10.1109/TVCG.2006.100 (DOI)
Available from: 2006-09-14 Created: 2006-09-14 Last updated: 2015-09-22
9. Full Body Virtual Autopsies Using A State-of-the-art Volume Rendering Pipeline
Open this publication in new window or tab >>Full Body Virtual Autopsies Using A State-of-the-art Volume Rendering Pipeline
Show others...
2006 (English)In: IEEE Transactions on Visualization and Computer Graphics, ISSN 1077-2626, E-ISSN 1941-0506, Vol. 12, no 5, 869-876 p.Article in journal (Other academic) Published
Abstract [en]

This paper presents a procedure for virtual autopsies based on interactive 3D visualizations of large scale, high resolutiondata from CT-scans of human cadavers. The procedure is described using examples from forensic medicine and the added valueand future potential of virtual autopsies is shown from a medical and forensic perspective. Based on the technical demands ofthe procedure state-of-the-art volume rendering techniques are applied and refined to enable real-time, full body virtual autopsiesinvolving gigabyte sized data on standard GPUs. The techniques applied include transfer function based data reduction using levelof-detail selection and multi-resolution rendering techniques. The paper also describes a data management component for large,out-of-core data sets and an extension to the GPU-based raycaster for efficient dual TF rendering. Detailed benchmarks of thepipeline are presented using data sets from forensic cases.

Keyword
Forensics, autopsies, medical visualization, volume rendering, large scale data
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-13950 (URN)10.1109/TVCG.2006.146 (DOI)000241383300028 ()
Available from: 2006-09-14 Created: 2006-09-14 Last updated: 2015-10-09

Open Access in DiVA

cover(333 kB)83 downloads
File information
File name COVER01.pdfFile size 333 kBChecksum SHA-1
25e849c6b2ad25f9b918acf957f7801fe65f3e036c4dffde8d4cf8cc1a9ce341c02df355
Type coverMimetype application/pdf
fulltext(2048 kB)2950 downloads
File information
File name FULLTEXT01.pdfFile size 2048 kBChecksum SHA-1
ef8bf7a1b442f6ee0a19efdf97d1cd1fcd5ad6e05e9e5c925b95b1e4c79927c48c8ef77e
Type fulltextMimetype application/pdf

Authority records BETA

Ljung, Patric

Search in DiVA

By author/editor
Ljung, Patric
By organisation
Visual Information Technology and Applications (VITA)The Institute of Technology
Computer Science

Search outside of DiVA

GoogleGoogle Scholar
Total: 2950 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 5333 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf