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

Direct link
Fused Multi-Volume DVR using Binary Space Partitioning
Linköping University, Department of Science and Technology, Visual Information Technology and Applications (VITA). Linköping University, The Institute of Technology.
Siemens Corporate Research.ORCID iD: 0000-0002-9288-5322
VRVis Research Center.
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
2009 (English)In: Computer graphics forum (Print), ISSN 0167-7055, E-ISSN 1467-8659, Vol. 28, no 3, 847-854 p.Article in journal (Refereed) Published
Abstract [en]

Multiple-volume visualization is a growing field in medical imaging providing simultaneous exploration of volumes acquired from varying modalities. However, high complexity results in an increased strain on performance compared to single volume rendering as scenes may consist of volumes with arbitrary orientations and rendering is performed with varying sample densities. Expensive image order techniques such as depth peeling have previously been used to perform the necessary calculations. In. this work we present a view-independent region based scene description for multi-volume pipelines. Using Binary Space Partitioning we are able to create a simple interface providing all required information for advanced multi-volume renderings while introducing a minimal overhead for scenes with few volumes. The modularity of our solution is demonstrated by the use of visual development and performance is documented with benchmarks and real-time simulations.

Place, publisher, year, edition, pages
2009. Vol. 28, no 3, 847-854 p.
National Category
Computer Engineering Computer Science
URN: urn:nbn:se:liu:diva-20144DOI: 10.1111/j.1467-8659.2009.01465.xOAI: diva2:233657
Available from: 2009-09-01 Created: 2009-08-31 Last updated: 2015-09-22
In thesis
1. Medical Volume Visualization Beyond Single Voxel Values
Open this publication in new window or tab >>Medical Volume Visualization Beyond Single Voxel Values
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Medical visualization involves many complex decisions for both the user and the imaging algorithms. This thesis aims to improve medical volume visualization through a series of technical contributions to aid such decision processes. Improvements are achieved by using more data, beyond single voxels, in the associated visual analyses.

Simultaneous visualization of multiple data sources and different data formats is rapidly becoming a necessity. This is due to both the growing number of data producing image acquisition techniques as well as the increase in geometric data representations that can be created. Maintaining high rendering performance under these circumstances is challenging, but necessary, to support an exploratory visualization process. This thesis proposes two algorithms to address this challenge: a multi-volume approach that applies binary-space partitioning to solve painters' algorithm geometrically and a rendering algorithm for hybrid data that improves the management of the available graphics memory.

Additional information for decision support is often derived from the captured image data. Classification techniques, in particular, often utilize secondary information sources or neighborhood analysis as means to improve specificity. One example is a proposed algorithm that improves visualization of blood vessels by automatically optimizing visualization parameters based on observed vesselness. This thesis also proposes algorithms involving neighborhood analysis, with a particular focus on domain specific classification knowledge provided by the user. One algorithm provides the ability to semantically state spatial relations between tissues based on encoded material information. Another algorithm improves the representation of discrete features by integrating the users' knowledge in the reconstruction step of the visualization pipeline.

Many of the methods proposed in this thesis can also be applied to other domains, but are all described here in the context of medical volume visualization as most of the research has been performed within this field.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2014. 79 p.
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1614
National Category
Computer and Information Science Computer Science Medical Image Processing
urn:nbn:se:liu:diva-110239 (URN)10.3384/diss.diva-110239 (DOI)978-91-7519-256-7 (print) (ISBN)
Public defence
2014-10-03, Domteatern, Visualiseringscenter C, Kungsgatan 54, Norrköping, 09:00 (English)
Available from: 2014-09-04 Created: 2014-09-04 Last updated: 2015-09-22Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Search in DiVA

By author/editor
Lindholm, StefanLjung, PatricYnnerman, Anders
By organisation
Visual Information Technology and Applications (VITA)The Institute of Technology
In the same journal
Computer graphics forum (Print)
Computer EngineeringComputer Science

Search outside of DiVA

GoogleGoogle Scholar
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

Altmetric score

Total: 245 hits
ReferencesLink to record
Permanent link

Direct link