Modeling White-Matter Fiber-Orientation Uncertainty for Improved Probabilistic Tractography

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Tractography uses fiber-orientation estimates to trace the likely paths of white-matter tracts through the brain, in order to map brain connectivity non-invasively. In this paper, we propose a novel probabilistic framework for modeling fiber-orientation uncertainty and improve probabilistic tractography. The main innovation in the present formulation consists in coupling a particle filtering process with a clustered-mixture model approach to model directional data. 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 technique is validated on simulated as well as on real human brain data experiments.
Original languageUnknown
Title of host publicationSCITEPRESS – Science and Technology Publications, INSTICC – Institute for Systems and Technologies of Information, Control and Communication
Pages71-78
DOIs
Publication statusPublished - 1 Jan 2014
EventNEUROTECHNIX 2014 – 2nd International Congress on Neurotechnology, Electronics and Informatics -
Duration: 1 Jan 2014 → …

Conference

ConferenceNEUROTECHNIX 2014 – 2nd International Congress on Neurotechnology, Electronics and Informatics
Period1/01/14 → …

Cite this

da Silva, A. R. F., & DEE Group Author (2014). Modeling White-Matter Fiber-Orientation Uncertainty for Improved Probabilistic Tractography. In SCITEPRESS – Science and Technology Publications, INSTICC – Institute for Systems and Technologies of Information, Control and Communication (pp. 71-78) https://doi.org/10.5220/0005069300710078
da Silva, Adelino Rocha Ferreira ; DEE Group Author. / Modeling White-Matter Fiber-Orientation Uncertainty for Improved Probabilistic Tractography. SCITEPRESS – Science and Technology Publications, INSTICC – Institute for Systems and Technologies of Information, Control and Communication. 2014. pp. 71-78
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title = "Modeling White-Matter Fiber-Orientation Uncertainty for Improved Probabilistic Tractography",
abstract = "Tractography uses fiber-orientation estimates to trace the likely paths of white-matter tracts through the brain, in order to map brain connectivity non-invasively. In this paper, we propose a novel probabilistic framework for modeling fiber-orientation uncertainty and improve probabilistic tractography. The main innovation in the present formulation consists in coupling a particle filtering process with a clustered-mixture model approach to model directional data. 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 technique is validated on simulated as well as on real human brain data experiments.",
keywords = "Diffusion MRI, Probabilistic Tractography, Particle Filtering",
author = "{da Silva}, {Adelino Rocha Ferreira} and {DEE Group Author}",
note = "Sem PDF",
year = "2014",
month = "1",
day = "1",
doi = "10.5220/0005069300710078",
language = "Unknown",
isbn = "978-989-758-056-7",
pages = "71--78",
booktitle = "SCITEPRESS – Science and Technology Publications, INSTICC – Institute for Systems and Technologies of Information, Control and Communication",

}

da Silva, ARF & DEE Group Author 2014, Modeling White-Matter Fiber-Orientation Uncertainty for Improved Probabilistic Tractography. in SCITEPRESS – Science and Technology Publications, INSTICC – Institute for Systems and Technologies of Information, Control and Communication. pp. 71-78, NEUROTECHNIX 2014 – 2nd International Congress on Neurotechnology, Electronics and Informatics, 1/01/14. https://doi.org/10.5220/0005069300710078

Modeling White-Matter Fiber-Orientation Uncertainty for Improved Probabilistic Tractography. / da Silva, Adelino Rocha Ferreira; DEE Group Author.

SCITEPRESS – Science and Technology Publications, INSTICC – Institute for Systems and Technologies of Information, Control and Communication. 2014. p. 71-78.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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T1 - Modeling White-Matter Fiber-Orientation Uncertainty for Improved Probabilistic Tractography

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AU - DEE Group Author

N1 - Sem PDF

PY - 2014/1/1

Y1 - 2014/1/1

N2 - Tractography uses fiber-orientation estimates to trace the likely paths of white-matter tracts through the brain, in order to map brain connectivity non-invasively. In this paper, we propose a novel probabilistic framework for modeling fiber-orientation uncertainty and improve probabilistic tractography. The main innovation in the present formulation consists in coupling a particle filtering process with a clustered-mixture model approach to model directional data. 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 technique is validated on simulated as well as on real human brain data experiments.

AB - Tractography uses fiber-orientation estimates to trace the likely paths of white-matter tracts through the brain, in order to map brain connectivity non-invasively. In this paper, we propose a novel probabilistic framework for modeling fiber-orientation uncertainty and improve probabilistic tractography. The main innovation in the present formulation consists in coupling a particle filtering process with a clustered-mixture model approach to model directional data. 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 technique is validated on simulated as well as on real human brain data experiments.

KW - Diffusion MRI

KW - Probabilistic Tractography

KW - Particle Filtering

U2 - 10.5220/0005069300710078

DO - 10.5220/0005069300710078

M3 - Conference contribution

SN - 978-989-758-056-7

SP - 71

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BT - SCITEPRESS – Science and Technology Publications, INSTICC – Institute for Systems and Technologies of Information, Control and Communication

ER -

da Silva ARF, DEE Group Author. Modeling White-Matter Fiber-Orientation Uncertainty for Improved Probabilistic Tractography. In SCITEPRESS – Science and Technology Publications, INSTICC – Institute for Systems and Technologies of Information, Control and Communication. 2014. p. 71-78 https://doi.org/10.5220/0005069300710078