Abstract #0350
On evaluating the accuracy and biological plausibility of diffusion MRI tractograms
David Romascano 1 , Alessandro Dal Pal 2 , Jean-Philippe Thiran 1,3 , and Alessandro Daducci 1,4
1
Signal Processing Laboratory (LTS5), cole
Polytechnique Fdrale de Lausanne, Lausanne, Vaud,
Switzerland,
2
Department
of Mathematics and Computer Science, University of
Parma, Parma, Italy,
3
Department
of Radiology, University Hospital Center and University
of Lausanne, Lausanne, Vaud, Switzerland,
4
Center
for Biomedical Imaging, Signal Processing Core,
Lausanne, Vaud, Switzerland
In diffusion MRI, traditional tractography algorithms do
not recover truly quantitative tractograms and the
structural connectivity has to be estimated indirectly
by counting the number of fiber tracts or averaging
scalar maps along them. Recently, global and efficient
methods have emerged to estimate more quantitative
tractograms by combining tractography with local models
for the diffusion signal, like the Convex Optimization
Modeling for Microstructure Informed Tractography
(COMMIT) framework. In this abstract, we show the
importance of using both (i) proper multi-compartment
diffusion models and (ii) adequate multi-shell
acquisitions, in order to evaluate the accuracy and the
biological plausibility of the tractograms.
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