An Improved Spectral Quaternion Interpolation Method of Diffusion Tensor Imaging_Journal of Biomedical Engineering

Authors：

 XUYonghong , GAOShangce , HAOXiaofei

Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China;

Corresponding author：

XUYonghong, Email: xyh@ysu.edu.cn

Keywords：

diffusion tensor imaging (DTI); interpolation; spectral decomposition; quaternion; anisotropy

DOI：

10.7507/1001-5515.20160061

Video：

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Diffusion tensor imaging (DTI) is a rapid development technology in recent years of magnetic resonance imaging. The diffusion tensor interpolation is a very important procedure in DTI image processing. The traditional spectral quaternion interpolation method revises the direction of the interpolation tensor and can preserve tensors anisotropy, but the method does not revise the size of tensors. The present study puts forward an improved spectral quaternion interpolation method on the basis of traditional spectral quaternion interpolation. Firstly, we decomposed diffusion tensors with the direction of tensors being represented by quaternion. Then we revised the size and direction of the tensor respectively according to different situations. Finally, we acquired the tensor of interpolation point by calculating the weighted average. We compared the improved method with the spectral quaternion method and the Log-Euclidean method by the simulation data and the real data. The results showed that the improved method could not only keep the monotonicity of the fractional anisotropy (FA) and the determinant of tensors, but also preserve the tensor anisotropy at the same time. In conclusion, the improved method provides a kind of important interpolation method for diffusion tensor image processing.

Citation： XUYonghong, GAOShangce, HAOXiaofei. An Improved Spectral Quaternion Interpolation Method of Diffusion Tensor Imaging. Journal of Biomedical Engineering, 2016, 33(2): 362-367. doi: 10.7507/1001-5515.20160061 Copy

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10.	BASSER P J, PIERPAOLI C. Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI[J]. J Magn Reson Ser B, 1996, 111(3):209-219.
11.	邵宇, 刘莹, 孙富春.基于Riemann度量的张量值图像各向异性插值[J].清华大学学报:自然科学版, 2012, 52(4):550-556.
12.	YANG Feng, ZHU Y M, MAGNIN I E, et al. Feature-based interpolation of diffusion tensor fields and application to human cardiac DT-MRI[J]. Med Image Anal, 2012, 16(2):459-481.

1. BASSER P J, MATTIELLO J, LEBIHAN D. MR diffusion tensor spectroscopy and imaging[J]. Biophys J, 1994, 66(1):259-267.
2. WESTIN C F, MAIER S E, MAMATA H, et al. Processing and visualization for diffusion tensor MRI[J]. Med Image Anal, 2002, 6(2):93-108.
3. 邵宇, 刘莹, 孙富春.张量值图像插值方法综述[J].中国图象图形学报, 2012, 17(10):1197-1205.
4. ZHUKOV L, BARR A H. Oriented tensor reconstruction:Tracing neural pathways from diffusion tensor MRI[C]//IEEE VISUALIZATION, 2002. VIS 2002. Boston, MA, USA, 2002:387-394.
5. RODRIGUEZ-FLORIDO M A, WESTIN C F, RUIZ-ALZOLA J. DT-MRI regularization using anisotropic tensor field filtering[C]//IEEE International Symposium on Biomedical Imaging:Nano to Macro, 2004. IEEE, 2004:336-339.
6. PENNEC X, FILLARD P, AYACHE N. A riemannian framework for tensor computing[J]. Int J Comput Vis, 2006, 66(1):41-66.
7. ARSIGNY V, FILLARD P, PENNEC X, et al. Log-Euclidean metrics for fast and simple calculus on diffusion tensors[J]. Magnetic Resonance in Medicine, 2006, 56(2):411-421.
8. FILLARD P. Riemannian processing of tensors for diffusion MRI and computational anatomy of the brain[D]. Nice:University of Nice-Sophia Antipolis, 2008.
9. COLLARD A, BONNABEL S, PHILLIPS C A. Anisotropy preserving DTI processing[J]. Int J Comput Vis, 2014, 107(1):58-74.
10. BASSER P J, PIERPAOLI C. Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI[J]. J Magn Reson Ser B, 1996, 111(3):209-219.
11. 邵宇, 刘莹, 孙富春.基于Riemann度量的张量值图像各向异性插值[J].清华大学学报:自然科学版, 2012, 52(4):550-556.
12. YANG Feng, ZHU Y M, MAGNIN I E, et al. Feature-based interpolation of diffusion tensor fields and application to human cardiac DT-MRI[J]. Med Image Anal, 2012, 16(2):459-481.

Journal of Biomedical Engineering

An Improved Spectral Quaternion Interpolation Method of Diffusion Tensor Imaging

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