Abstract
We propose a novel post processing method for visualization of fiber traces from DT-MRI data. Using a recently proposed non-linear dimensionality reduction technique, Laplacian eigenmaps [3], we create a mapping from a set of fiber traces to a low dimensional Euclidean space. Laplacian eigenmaps constructs this mapping so that similar traces are mapped to similar points, given a custom made pairwise similarity measure for fiber traces. We demonstrate that when the low-dimensional space is the RGB color space, this can be used to visualize fiber traces in a way which enhances the perception of fiber bundles and connectivity in the human brain.
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Brun, A., Park, HJ., Knutsson, H., Westin, CF. (2003). Coloring of DT-MRI Fiber Traces Using Laplacian Eigenmaps. In: Moreno-Díaz, R., Pichler, F. (eds) Computer Aided Systems Theory - EUROCAST 2003. EUROCAST 2003. Lecture Notes in Computer Science, vol 2809. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45210-2_47
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DOI: https://doi.org/10.1007/978-3-540-45210-2_47
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-20221-9
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