Tracking the Cortico-Spinal Tract as a Multi-Modal Distribution of Streamlines from Local White Matter Microstructure Models

Aymeric Stamm 1, * Olivier Commowick 2 Xavier Tomas-Fernandez 1 Jolene Singh 1 Simon K. Warfield 1
* Auteur correspondant
1 CRL - Computational Radiology Laboratory [Boston]
2 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
Abstract : We present a pipeline to reconstruct the corticospinal tract (CST) that connects the spinal cord to the motor cortex. The proposed method combines a new white matter microstructure model coined Diffusion Directions Imaging and a new tractography algorithm based on a particle filter adapted for approximating multi-modal distributions. In this paper, we put the computation time and accuracy of our pipeline to the test in the context of the MICCAI 2014 DTI challenge, which aims to provide fast and accurate reconstructions of the CST for presurgical planning of brain tumor extraction. These two key performance metrics are expected in such a situation where time is of the essence and the quality of the data is dependent on the patient's health condition and ability to cooperate. In no more than 1.5 hours per patient, we successfully provide accurate CSTs of 2 very collaborative patients who underwent a diffusion MRI protocol that included 69 diffusion-sensitizing gradients spread over 4 different shells ranging from b = 200 to b = 3000 s/mm2.
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Communication dans un congrès
MICCAI Challenge on DTI Tractography Proceedings, Sep 2014, Boston, United States. pp.21-32, 2014
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Soumis le : lundi 22 septembre 2014 - 17:30:16
Dernière modification le : mercredi 13 février 2019 - 09:46:02
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Aymeric Stamm, Olivier Commowick, Xavier Tomas-Fernandez, Jolene Singh, Simon K. Warfield. Tracking the Cortico-Spinal Tract as a Multi-Modal Distribution of Streamlines from Local White Matter Microstructure Models. MICCAI Challenge on DTI Tractography Proceedings, Sep 2014, Boston, United States. pp.21-32, 2014. 〈inserm-01066812v2〉

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