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Efficient Medical Volume Visualization: An Approach Based on Domain Knowledge
Linköping University, Department of Science and Technology, Visual Information Technology and Applications (VITA). Linköping University, The Institute of Technology.ORCID iD: 0000-0002-9368-0177
2007 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Direct Volume Rendering (DVR) is a visualization technique that has proved to be a very powerful tool in many scientific visualization applications. Diagnostic medical imaging is one domain where DVR could provide clear benefits in terms of unprecedented possibilities for analysis of complex cases and highly efficient work flow for certain routine examinations. The full potential of DVR in the clinical environment has not been reached, however, primarily due to limitations in conventional DVR methods and tools.

This thesis presents methods addressing four major challenges for DVR in clinical use. The foundation of all methods is to incorporate the domain knowledge of the medical professional in the technical solutions. The first challenge is the very large data sets routinely produced in medical imaging today. To this end a multiresolution DVR pipeline is proposed, which dynamically prioritizes data according to the actual impact in the rendered image to be reviewed. Using this prioritization the system can reduce the data requirements throughout the pipeline and provide high performance and visual quality in any environment.

Another problem addressed is how to achieve simple yet powerful interactive tissue classification in DVR. The methods presented define additional attributes that effectively captures readily available medical knowledge. The task of tissue detection is also important to solve in order to improve efficiency and consistency of diagnostic image review. Histogram-based techniques that exploit spatial relations in the data to achieve accurate and robust tissue detection are presented in this thesis.

The final challenge is uncertainty visualization, which is very pertinent in clinical work for patient safety reasons. An animation method has been developed that automatically conveys feasible alternative renderings. The basis of this method is a probabilistic interpretation of the visualization parameters.

Several clinically relevant evaluations of the developed techniques have been performed demonstrating their usefulness. Although there is a clear focus on DVR and medical imaging, most of the methods provide similar benefits also for other visualization techniques and application domains.

Place, publisher, year, edition, pages
Institutionen för teknik och naturvetenskap , 2007. , 55 p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1125
Keyword [en]
Scientific Visualization, Medical Imaging, Computer Graphics, Volume Rendering, Transfer Function, Level-of-detail, Fuzzy Classification, Uncertainty Visualization, Virtual Autopsies
National Category
Medical Laboratory and Measurements Technologies
Identifiers
URN: urn:nbn:se:liu:diva-9561ISBN: 978-91-85831-10-4 (print)OAI: oai:DiVA.org:liu-9561DiVA: diva2:23985
Public defence
2007-09-14, Berzeliussalen, Hälsouniversitetet, Linköping, 13:15 (English)
Opponent
Supervisors
Available from: 2007-08-24 Created: 2007-08-24 Last updated: 2015-09-22
List of papers
1. 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
2. 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
3. Standardized volume rendering for magnetic resonance angiography measurements in the abdominal aorta
Open this publication in new window or tab >>Standardized volume rendering for magnetic resonance angiography measurements in the abdominal aorta
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2006 (English)In: Acta Radiologica, ISSN 0284-1851, E-ISSN 1600-0455, Vol. 47, no 2, 172-178 p.Article in journal (Refereed) Published
Abstract [en]

Purpose: To compare three methods for standardizing volume rendering technique (VRT) protocols by studying aortic diameter measurements in magnetic resonance angiography (MRA) datasets.

Material and Methods: Datasets from 20 patients previously examined with gadolinium-enhanced MRA and with digital subtraction angiography (DSA) for abdominal aortic aneurysm were retrospectively evaluated by three independent readers. The MRA datasets were viewed using VRT with three different standardized transfer functions: the percentile method (Pc-VRT), the maximum-likelihood method (ML-VRT), and the partial range histogram method (PRH-VRT). The aortic diameters obtained with these three methods were compared with freely chosen VRT parameters (F-VRT) and with maximum intensity projection (MIP) concerning inter-reader variability and agreement with the reference method DSA.

Results: F-VRT parameters and PRH-VRT gave significantly higher diameter values than DSA, whereas Pc-VRT gave significantly lower values than DSA. The highest interobserver variability was found for F-VRT parameters and MIP, and the lowest for Pc-VRT and PRH-VRT. All standardized VRT methods were significantly superior to both MIP and F-VRT in this respect. The agreement with DSA was best for PRH-VRT, which was the only method with a mean error below 1 mm and which also had the narrowest limits of agreement (95% of cases between 2.1 mm below and 3.1 mm above DSA).

Conclusion: All the standardized VRT methods compare favorably with MIP and VRT with freely selected parameters as regards interobserver variability. The partial range histogram method, although systematically overestimating vessel diameters, gives results closest to those of DSA.

Keyword
Abdominal aortic aneurysm (AAA); angiography; magnetic resonance angiography (MRA); maximum intensity projection (MIP); volume rendering technique (VRT); user dependence
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-14591 (URN)10.1080/02841850500445298 (DOI)000236669500010 ()
Available from: 2007-08-24 Created: 2007-08-24 Last updated: 2017-12-13Bibliographically approved
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
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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. 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
7. 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: 2017-12-13
8. 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: 2017-12-13
9. Uncertainty Visualization in Medical Volume Rendering Using Probabilistic Animation
Open this publication in new window or tab >>Uncertainty Visualization in Medical Volume Rendering Using Probabilistic Animation
2007 (English)In: IEEE Transactions on Visualization and Computer Graphics, ISSN 1077-2626, E-ISSN 1941-0506, Vol. 13, no 6, 1648-1655 p.Article in journal (Refereed) Published
Abstract [en]

Direct volume rendering has proved to be an effective visualization method for medical data sets and has reached wide-spread clinical use. The diagnostic exploration, in essence, corresponds to a tissue classification task, which is often complex and time-consuming. Moreover, a major problem is the lack of information on the uncertainty of the classification, which can have dramatic consequences for the diagnosis. In this paper this problem is addressed by proposing animation methods to convey uncertainty in the rendering. The foundation is a probabilistic Transfer Function model which allows for direct user interaction with the classification. The rendering is animated by sampling the probability domain over time, which results in varying appearance for uncertain regions. A particularly promising application of this technique is a "sensitivity lens" applied to focus regions in the data set. The methods have been evaluated by radiologists in a study simulating the clinical task of stenosis assessment, in which the animation technique is shown to outperform traditional rendering in terms of assessment accuracy.

Keyword
uncertainty, medical visualization, probability, transfer function, volume rendering
National Category
Medical Laboratory and Measurements Technologies
Identifiers
urn:nbn:se:liu:diva-14597 (URN)10.1109/TVCG.2007.70518 (DOI)000250401100076 ()
Available from: 2007-08-24 Created: 2007-08-24 Last updated: 2017-12-13

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