Abstract
abstract Tensor valued data are frequently used in medical imaging. For a 3-dimensional second order tensor such data imply at least six degrees of freedom for each voxel. The operators ability to perceive this information is of outmost importance and in many cases a limiting factor for the interpretation of the data. In this paper we propose a decomposition of such tensor fields using the Tflash tensor glyphs that intuitively conveys important tensor features to a human observer. A matlab implementation for visualization of single tensors are described in detail and a VTK/ITK implementation for visualization of tensor fields have been developed as a Medical Studio component.
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References
G. H. Granlund and H. Knutsson. Signal Processing for Computer Vision. Kluwer Academic Publishers, 1995.
Gordon Kindlmann. Superquadric tensor glyphs. In Proceeding of The Joint Eurographics - IEEE TCVG Symposium on Visualization, pages 147–154, May 2004.
Gordon Kindlmann. Visualization and Analysis of Diffusion Tensor Fields. PhD thesis, University of Utah, 2004.
H. Knutsson. Representing local structure using tensors. In R. Petchimuthu (eds.) The 6th Scandinavian Conference on Image Analysis, pages 244–251, Oulu, Finland, June 1989. Report LiTH–ISY–I–1019, Computer Vision Laboratory, Linköping University, Sweden, 1989.
V. Nicolas and B. Macq. Medical Studio. http://www.medicalstudio.org.
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© 2009 Springer-Verlag London Limited
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Wiklund, J., Nicolas, V., Rondao, P., Andersson, M., Knutsson, H. (2009). T-flash: Tensor Visualization in Medical Studio. In: Aja-Fernández, S., de Luis García, R., Tao, D., Li, X. (eds) Tensors in Image Processing and Computer Vision. Advances in Pattern Recognition. Springer, London. https://doi.org/10.1007/978-1-84882-299-3_21
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DOI: https://doi.org/10.1007/978-1-84882-299-3_21
Publisher Name: Springer, London
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