Interpolation and Averaging of Multi-Compartment Model Images

Renaud Hedouin 1, * Olivier Commowick 1 Aymeric Stamm 2 Christian Barillot 1
* Corresponding author
1 VisAGeS - Vision, Action et Gestion d'informations en Santé
INSERM - Institut National de la Santé et de la Recherche Médicale : U746, Inria Rennes – Bretagne Atlantique , IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
2 CRL - Computational Radiology Laboratory [Boston]
Abstract : 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.
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https://www.hal.inserm.fr/inserm-01185733
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Submitted on : Thursday, October 15, 2015 - 10:11:28 AM
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Renaud Hedouin, Olivier Commowick, Aymeric Stamm, Christian Barillot. Interpolation and Averaging of Multi-Compartment Model Images. 18th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Oct 2015, Munich, Germany. pp.354-362, ⟨10.1007/978-3-319-24571-3_43⟩. ⟨inserm-01185733⟩

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