Journal of Korea Multimedia Society (한국멀티미디어학회논문지)

Korea Multimedia Society (한국멀티미디어학회)
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Algorithm Selection Method for Efficient Maximum Intensity Projection Based on User Preference

사용자 선호에 기반한 효율적 최대 휘소 가시화 알고리즘의 선택 방법

  • Received : 2018.01.10
  • Accepted : 2018.01.22
  • Published : 2018.02.28
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Abstract

Maximum intensity projection (MIP) is a common visualization technique in medical imaging system. A typical method to improve the performance of MIP is empty space leaping, which skips unnecessary area. This research proposes a new method to improve the existing empty space leaping. In order to skip more regions, we introduce a variety of acceleration strategies that use some tolerance given by the user to take part in image quality loss. Each proposed method shows various image quality and speed, and this study compares them to select the best one. Experimental results show that it is most efficient to add a constant tolerance function when the image quality required by the user is low. Conversely, when the user required image quality is high, a function with a low tolerance of volume center is most effective. Applying the proposed method to general MIP visualization can generate a relatively high quality image in a short time.

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References

  1. P. Sabella, "A Rendering Algorithm for Visualizing 3D Scalar Fields," Proceedings of the 15th Annual Conference on Computer Graphics and Interactive Techniques, ACM SIGGRAPH 1988, pp. 51-58, 1988.
  2. S. Schreiner and R.L. Galloway, “A Fast Maximum-Intensity Projection Algorithm for Generating Magnetic Resonance Angiograms,” IEEE Transactions on Medical Imaging, Vol. 12, No. 1, pp. 50-57, 1993. https://doi.org/10.1109/42.222666
  3. L. Mroz, A. Konig, and E. Groller, "Real-Time Maximum Intensity Projection," Proceedings of the Joint EUROGRAPHICS-IEEE TCCG Symposium on Visualization, Data Visualization '99, pp. 135-144, 1999.
  4. L. Fang, Y. Wang, B. Qiu, and Y. Qian, “Fast Maximum Intensity Projection Algorithm Using Shear Warp Factorization and Reduced Resampling,” Magnetic Resonance in Medicine, Vol. 47, No. 4, pp. 696-700, 2002. https://doi.org/10.1002/mrm.10114
  5. H. Kye, S. Lee, and J. Lee, "CPU-Based Real-Time Maximim Intensity Projection Via Fast Matrix Transposition Using Parallelization Operations with the AVX Instruction Set," Multimedia Tools and Applications, pp. 1-1, 2017.
  6. M. Levoy, “Display of Surfaces from Volume Data,” IEEE Computer Graphics and Applications, Vol. 8, No. 3, pp. 29-37, 1988. https://doi.org/10.1109/38.511
  7. G. Kiefer, H. Lehmann, and J. Weese, “Fast Maximum Intensity Projections of Large Medical Data Sets by Exploiting Hierarchical Memory Architectures,” IEEE Transactions on Information Technology in Biomedicine, Vol. 10, No. 2, pp. 385-394, 2006. https://doi.org/10.1109/TITB.2005.863871
  8. H. Kye and J. Kim, “Acceleration Techniques for GPGPU-Based Maximum Intensity Projection,” Journal of Korea Multimedia Society, Vol. 14, No. 8, pp. 981-991, 2011. https://doi.org/10.9717/kmms.2011.14.8.981
  9. H. Kye, B. Sohn, and J. Lee, “Interactive GPU-Based Maximum Intensity Projection of Large Medical Data Sets Using Visibility Culling Based on the Initial Occluder and the Visible Block Classification,” Computerized Medical Imaging and Graphics, Vol. 36, No. 5, pp. 366-374, 2012. https://doi.org/10.1016/j.compmedimag.2012.04.001
  10. L. Mroz, H. Hauser, and E. Groller, “Interactive High-Quality Maximum Intensity Projection,” Computer Graphics forum, Vol. 19, No. 3, pp. 341-350, 2000. https://doi.org/10.1111/1467-8659.00426
  11. M. Levoy, “Efficient Ray Tracing of Volume Data,” ACM Transactions on Graphics, Vol. 9, No. 3, pp. 245-261, 1990. https://doi.org/10.1145/78964.78965
  12. H. Kye and D. Jeong, “Accelerated MIP Based on GPU Using Block Clipping and Occlusion Query,” Computers and Graphics, Vol. 32, No. 3, pp. 283-292, 2008. https://doi.org/10.1016/j.cag.2007.12.002
  13. O. Kwon, S. Kang, S. Kim, Y. Kim, and Y.G. Shin, "Maximum Intensity Projection Using Bidirectional Compositing with Block Skipping," Journal of X-ray Science and Technology Vol. 23, No. 1, pp. 33-44, 2015.
  14. B. Mora and D.S. Ebert, “Low-Complexity Maximum Intensity Projection,” ACM Transactions on Graphics, Vol. 24, No. 4, pp. 1392-1416, 2005. https://doi.org/10.1145/1095878.1095886
  15. V. Pekar, D. Hempel, G. Kiefer, M. Busch, and J. Weese, "Efficient Visualization of Large Medical Image Datasets on Standard PC Hardware," Proceedings of Joint EUROGRAPHICS, IEEE TCVG Symposium on Visualization, pp. 135-140, 2003.
  16. K. Kim and H. Park, “A Fast Progressive Method of Maximum Intensity Projection,” Computerized Medical Imaging and Graphics, Vol. 25, No. 5, pp. 433-441, 2001. https://doi.org/10.1016/S0895-6111(01)00003-9