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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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