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Metrics for Uncertainty Analysis and Visualization of Diffusion Tensor Images

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6326))

Abstract

In this paper, we propose three metrics to quantify the differences between the results of diffusion tensor magnetic resonance imaging (DT-MRI) fiber tracking algorithms: the area between corresponding fibers of each bundle, the Earth Mover’s Distance (EMD) between two fiber bundle volumes, and the current distance between two fiber bundle volumes. We also discuss an interactive fiber track comparison visualization toolkit we have developed based on the three proposed fiber difference metrics and have tested on six widely-used fiber tracking algorithms. To show the effectiveness and robustness of our metrics and visualization toolkit, we present results on both synthetic data and high resolution monkey brain DT-MRI data. Our toolkit can be used for testing the noise effects on fiber tracking analysis and visualization and to quantify the difference between any pair of DT-MRI techniques, compare single subjects within an image atlas.

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Jiao, F. et al. (2010). Metrics for Uncertainty Analysis and Visualization of Diffusion Tensor Images . In: Liao, H., Edwards, P.J."., Pan, X., Fan, Y., Yang, GZ. (eds) Medical Imaging and Augmented Reality. MIAR 2010. Lecture Notes in Computer Science, vol 6326. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15699-1_19

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  • DOI: https://doi.org/10.1007/978-3-642-15699-1_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15698-4

  • Online ISBN: 978-3-642-15699-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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