Abstract
The Visible Human™ is a vast resource, which few methods can fully explore and analyze. We aim to completely label and volume display it; here we discuss the main obstacles, and our means for overcoming them. Our segmentation into over 350 anatomical regions spans the various body systems. Volume rendering by a memory-independent, partitioned, color and translucency scheme gives realistic human images, with many possibilities for medical education and “edutainment”.
The authors thank Tim Poston and Raghu Raghavan for their valuable technical and editorial comments. We are grateful to Ms. Jin Xiaoyang and all the NUS students who enthusiastically segmented the data with great patience and precision. We also express our gratitude to Chun Pong Yu and Pingli Pang who developed the keyframe animation, and built and integrated the GUI for the rendering system. Thanks to Seema Mullick for her support in segmenting data and in matters related to design aesthetics. This work would not have been possible without the support of the National Institutes of Health for the Visible Human Project.
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References
Spitzer, V. et al.: The Visible Human Male: A Technical Report. Journal of American Medical Informatics Association (1995)
http://www.nlm.nih.gov/extramural_research.dir/visible_human.html
Pavlidis, T.: Algorithms for Graphics and Image Processing. Computer Science Press, Rockville, MD, (1982).
Levoy, M.: Display of surfaces from Volume Data. IEEE Computer Graphics and Applications. 8.5 (1988) 29–37
Nguyen, H. T., Srinivasan R.: PaVe4-16: A Distributed Volume Visualization Technique. TR94-135-0 Technical Report, Inst. of Sys. Science, National Univ. of Singapore, Singapore (1993)
Jain, A. K.: Fundamentals of Digital Image Processing. Prentice Hall, Englewood Cliffs, NJ (1989)
Monga, O., Deriche, R., Malandain, G., Cocquerez: Recursive filtering and edge closing: 2 primary tools for 3D edge detection. Image and Vision Comp., 9.4 (1991)
Nguyen, H. T., Mullick R., Srinivasan, R.: Partitioned Volume Rendering (ParVo): An efficient approach to visualizing large datasets. Manuscript in preparation.
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© 1996 Springer-Verlag Berlin Heidelberg
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Mullick, R., Nguyen, H.T. (1996). Visualization and labeling of the Visible Human™ dataset: Challenges & resolves. In: Höhne, K.H., Kikinis, R. (eds) Visualization in Biomedical Computing. VBC 1996. Lecture Notes in Computer Science, vol 1131. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0046938
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DOI: https://doi.org/10.1007/BFb0046938
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