Coloring of DT-MRI Fiber Traces Using Laplacian Eigenmaps

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.

• Type: Conference
• Year: 2003
• Where: EUROCAST
• Authors: Anders Brun, Hae-Jeong Park, Hans Knutsson, Carl-Fredrik Westin
• Keywords: EUROCAST 2003, Laplacian Eigenmaps, Laplacian Eigenmaps Constructs, fiber Traces