Multi-compartment diffusion models (MCM) are increasingly used to characterize the brain white matter microstructure from diffusion MRI. We address the problem of interpolation and averaging of MCM images as a simplification problem based on spectral clustering. As a core part of the framework, we propose novel solutions for the averaging of MCM compartments. Evaluation is performed both on synthetic and clinical data, demonstrating better performance for the “covariance analytic” averaging method. We then present an MCM template of normal controls constructed using the proposed interpolation.
CITATION STYLE
Hédouin, R., Commowick, O., Stamm, A., & Barillot, C. (2015). Interpolation and averaging of multi-compartment model images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9350, pp. 354–362). Springer Verlag. https://doi.org/10.1007/978-3-319-24571-3_43
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