GPU-based ray-casting of non-rigid deformations: a comparison between direct and indirect approaches
2014 (English)In: Proceedings of SIGRAD 2014, Visual Computing, June 12-13, 2014, Göteborg, Sweden / [ed] Mohammad Obaid; Daniel Sjölie; Erik Sintorn; Morten Fjeld, Linköping University Electronic Press, 2014, 67-74 p.Conference paper (Refereed)
For ray-casting of non-rigid deformations, the direct approach (as opposed to the traditional indirect approach) does not require the computation of an intermediate volume to be used for the rendering step. The aim of this study was to compare the two approaches in terms of performance (speed) and accuracy (image quality).
The direct and the indirect approach were carefully implemented to benefit of the massive GPU parallel power, using CUDA. They were then tested with Computed Tomography (CT) datasets of varying sizes and with a synthetic image, the Marschner-Lobb function.
The results show that the direct approach is dependent on the ray sampling steps, number of landmarks and image resolution. The indirect approach is mainly affected by the number of landmarks, if the volume is large enough.
These results exclude extreme cases, i.e. if the sampling steps are much smaller than the voxel size and if the image resolution is much higher than the ones used here. For a volume of size 512×512×512, using 100 landmarks and image resolution of 1280×960, the direct method performs better if the ray sampling steps are approximately above 1 voxel. Regarding accuracy, the direct method provides better results for multiple frequencies using the Marschner-Lobb function.
The conclusion is that the indirect method is superior in terms of performance, if the sampling along the rays is high, in comparison to the voxel grid, while the direct is superior otherwise. The accuracy analysis seems to point out that the direct method is superior, in particular when the implicit function is used.
Place, publisher, year, edition, pages
Linköping University Electronic Press, 2014. 67-74 p.
Linköping Electronic Conference Proceedings, ISSN 1650-3686 (print), 1650-3740 (online) ; 106
Computer Vision and Robotics (Autonomous Systems)
IdentifiersURN: urn:nbn:se:liu:diva-107553ISBN: 9789175192123OAI: oai:DiVA.org:liu-107553DiVA: diva2:725259
Swedish Computer Graphics Association (SIGRAD), Göteborg, Sweden, June 12-13, 2014