Brodlie, KW

Cohen, M

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promoting access to White Rose research papersWhite Rose Research Onlineeprints@whiterose.ac.ukUniversities of Leeds, Sheffield and Yorkhttp://eprints.whiterose.ac.uk/This is an author produced version of a conference abstract published inProceedings of Medical Image Understanding and Analysis 2007White Rose Research Online URL for this paper:http://eprints.whiterose.ac.uk/id/eprint/78003Paper:Cohen, M and Brodlie, KW (2007) Improving insight in medical volume rendering.In: Zwiggelaar, R and Labrosse, F, (eds.) Proceedings of Medical ImageUnderstanding and Analysis 2007. Medical Image Understanding and Analysis2007, 17th-18th July 2007, Aberystwyth. BMVA , 216 - 217.Improving Insight in Medical Volume RenderingKen Brodliea and Marcelo Cohenb∗aSchool of Computing, University of Leeds, UK, bPUCRS, BrazilExtended AbstractVolume rendering is now a well established technique for the display of three-dimensional volumetric data. Thefundamental idea is to model the dataset as a heterogeneous gel-like material whose colour and opacity at any pointis determined by a mapping, or transfer function, of the data value. The gel is then rendered using computer graphicstechniques such as ray casting.The technique has had some success in medical visualization although it remains quite common for clinicians to prefersequences of 2D images. This challenge has spurred the visualization community to seek improvements to the basicvolume rendering technique, and some of these improvements will be discussed in the talk.A difficulty until recently has been the speed at which volume rendered images can be created. Ray casting using CPUtechnology is slow and does not allow real-time interaction by changing the viewing direction for example. This hasdramatically changed in the last few years with the advent of GPU technology. The data can be stored as a 3D textureand fast GPU-based texture rendering now allows interactive volume rendering on commodity hardware. An excellentoverview of this area is provided by the IEEE Visualization tutorial [1].The improved hardware performance has been accompanied by an investigation of new algorithmic techniques. Muchof this comes from study of traditional medical illustration, where special effects are used to enhance the communi-cation of important detail. Rather than try to reproduce reality, medical illustrators focus on a more abstract approachthis can be traced back to Leonardo da Vinci who used exploded views to illustrate a baby in a womb.Thus illustrative volume rendering has become an important research topic. It has been explored from two directions:geometric effects, where the picture is distorted to highlight some area, or feature, of interest; and rendering effects,where effectively the colour and opacity of the gel is modified in order to highlight some particular features. In factmost of the ideas combine elements of each approach. A simple but vital geometric effect is an ability to clip awayparts of the volume that are not of interest.The talk will review these algorithmic developments in general. Pioneering work on rendering effects was carried outby Rheingans and Ebert [2], where they showed that non-photorealistic effects such as silhouette enhancement canincrease our ability to comprehend medical image data. Again an excellent starting point for study in this area is anIEEE Visualization tutorial [3]. An important recent paper is by Bruckner et al [4] where the opacity is modulated soas to make important regions more opaque, and less important more transparent.For a study of geometric effects we look in detail at one particular piece of work by ourselves at Leeds. This adoptsthe focus and context principle first put forward for two-dimensional presentation in information visualization. Theidea is simple: often there is some area within the image that one wants to explore in detail, but by zooming inwe lose the overall picture. In focus and context, we enlarge the focus region but retain a reduced size surroundingregion to maintain context. This idea transfers quite readily to 3D, and has been found useful in the visualization ofcerebral aneurysms from CTA data. A box can be defined around the aneurysm as the focus, and the data distortedso as to enlarge the box area and compress the remainder. Three styles of distortion can be applied: bifocal (as justdescribed); fish-eye, where there is a continuous decrease in magnification from a specified focus point; and a volumelens, simulating a magnifying glass, where the focus region is magnified, the surrounding area is left unchanged, andthere is a steep transition between the two.This work is fundamentally a geometric approach. However it is enhanced by a number of rendering effects, such asmodifying the opacity of a voxel according to its position relative to the focus region, or its relation to the viewingdirection. Another useful effect is to highlight the focus region by colorisation. An evaluation by the neurosurgeryteam at Leeds General Infirmary was very positive perhaps surprisingly the geometric distortion did not cause anyconcern to the surgeons (although an interventional radiologist was less enthusiastic about this aspect).∗kwb@comp.leeds.ac.uk; marcelo.cohen@pucrs.brFigure 1. Focus and context visualization of a cerebral aneurysmA key feature of the work is its careful exploitation of the GPU. The distortion is calculated by the CPU but stored as atexture and then used by the GPU in rendering. The figure shows an example of the work. Full details are in MarceloCohen’s thesis [5]References1. M. Hadwiger. “Introduction to GPU volume rendering.”, 2003. See http://www.vis.uni-stuttgart.de/vis03 tutorial/hadwiger gpu volrend2.pdf.2. P. Rheingans & D. Ebert. “Volume illustration: Nonphotorealistic rendering of volume models.” IEEE Transactions on Visual-ization and Computer Graphics 7(3), pp. 253–264, 2001.3. I. Viola, M. E. Groller, K. Buhler et al. “Illustrative visualization.”, 2005. Seehttp://www.cg.tuwien.ac.at/research/publications/2005/Viola-vistutillustrativevis/.4. S. Bruckner, S. Grimm, A. Kanitsar et al. “Illustrative context-preserving exploration of volume data.” IEEE Transactions onVisualization and Computer Graphics 12(6), pp. 1–11, 2006.5. M. Cohen. Focus and context in volume visualization. Ph.D. thesis, School of Computing, University of Leeds, 2006.

Improving insight in medical volume rendering

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