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Probabilistic Tractography Using Particle Filtering and Clustered Directional Data

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Advances in Neurotechnology, Electronics and Informatics

Part of the book series: Biosystems & Biorobotics ((BIOSYSROB,volume 12))

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Abstract

The approach of using deterministic methods to trace white-matter fiber tracts through the brain and map brain connectivity is pervasive in currently followed tractographic methodologies. However, using deterministic procedures to support fiber mapping jeopardizes rigorous fiber tractography and may originate deficient maps of white matter fiber networks. We propose a new probabilistic framework for modeling fiber-orientation uncertainty and improve probabilistic tractography. A probabilistic methodology is proposed for estimating intravoxel principal fiber directions, based on clustering directional data arising from orientation distribution function profiles. Mixtures of von Mises-Fisher (vMF) distributions are used to support the probabilistic estimation of intravoxel fiber directions. The fitted parameters of the clustered vMF mixture at each voxel are then used to estimate white-matter pathways using particle filtering techniques. The proposed method is validated on synthetic simulations, as well as on real data experiments. The method holds promise to support robust tractographic methodologies, and build realistic models of white matter tracts in the human brain.

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Authors and Affiliations

  1. NOVA CTS, Dep. de Eng. Electrotécnica, Faculdade de Ciências e Tecnologia, FCT, Universidade NOVA de Lisboa, 2829-516, Caparica, Portugal

    Adelino R. Ferreira da Silva

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  1. Adelino R. Ferreira da Silva
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Correspondence to Adelino R. Ferreira da Silva .

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Editors and Affiliations

  1. Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal

    Ana Rita Londral

  2. Faculty of Engineering, Universidade Católica Portuguesa, Lisbon, Portugal

    Pedro Encarnação

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da Silva, A.R.F. (2016). Probabilistic Tractography Using Particle Filtering and Clustered Directional Data. In: Londral, A., Encarnação, P. (eds) Advances in Neurotechnology, Electronics and Informatics. Biosystems & Biorobotics, vol 12. Springer, Cham. https://doi.org/10.1007/978-3-319-26242-0_4

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  • DOI: https://doi.org/10.1007/978-3-319-26242-0_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26240-6

  • Online ISBN: 978-3-319-26242-0

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