Structural connectivity analysis using finsler geometry

Tom Dela Haije; Peter Savadjiev; Andrea Fuster; Robert T. Schultz; Ragini Verma; Luc Florack; Carl Fredrik Westin

doi:10.1137/18M1209428

Structural connectivity analysis using finsler geometry

Tom Dela Haije, Peter Savadjiev, Andrea Fuster, Robert T. Schultz, Ragini Verma, Luc Florack, Carl Fredrik Westin

Datalogisk Institut

1 Citationer (Scopus)

Abstract

In this work we demonstrate how Finsler geometry---and specifically the related geodesic tracto-graphy---can be levied to analyze structural connections between different brain regions. We present new theoretical developments which support the definition of a novel Finsler metric and associated connectivity measures, based on closely related works on the Riemannian framework for diffusion MRI. Using data from the Human Connectome Project, as well as population data from an autism spectrum disorder study, we demonstrate that this new Finsler metric, together with the new connectivity measures, results in connectivity maps that are much closer to known tract anatomy compared to previous geodesic connectivity methods. Our implementation can be used to compute geodesic distance and connectivity maps for segmented areas and is publicly available.

Originalsprog	Engelsk
Tidsskrift	SIAM Journal on Imaging Sciences
Vol/bind	12
Udgave nummer	1
Sider (fra-til)	551-575
Antal sider	25
ISSN	1936-4954
DOI	https://doi.org/10.1137/18M1209428
Status	Udgivet - 2019

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title = "Structural connectivity analysis using finsler geometry",

abstract = "In this work we demonstrate how Finsler geometry---and specifically the related geodesic tracto-graphy---can be levied to analyze structural connections between different brain regions. We present new theoretical developments which support the definition of a novel Finsler metric and associated connectivity measures, based on closely related works on the Riemannian framework for diffusion MRI. Using data from the Human Connectome Project, as well as population data from an autism spectrum disorder study, we demonstrate that this new Finsler metric, together with the new connectivity measures, results in connectivity maps that are much closer to known tract anatomy compared to previous geodesic connectivity methods. Our implementation can be used to compute geodesic distance and connectivity maps for segmented areas and is publicly available.",

keywords = "Connectivity analysis, Diffusion MRI, Finsler geometry",

author = "{Dela Haije}, Tom and Peter Savadjiev and Andrea Fuster and Schultz, {Robert T.} and Ragini Verma and Luc Florack and Westin, {Carl Fredrik}",

year = "2019",

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language = "English",

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T1 - Structural connectivity analysis using finsler geometry

AU - Dela Haije, Tom

AU - Savadjiev, Peter

AU - Fuster, Andrea

AU - Schultz, Robert T.

AU - Verma, Ragini

AU - Florack, Luc

AU - Westin, Carl Fredrik

PY - 2019

Y1 - 2019

N2 - In this work we demonstrate how Finsler geometry---and specifically the related geodesic tracto-graphy---can be levied to analyze structural connections between different brain regions. We present new theoretical developments which support the definition of a novel Finsler metric and associated connectivity measures, based on closely related works on the Riemannian framework for diffusion MRI. Using data from the Human Connectome Project, as well as population data from an autism spectrum disorder study, we demonstrate that this new Finsler metric, together with the new connectivity measures, results in connectivity maps that are much closer to known tract anatomy compared to previous geodesic connectivity methods. Our implementation can be used to compute geodesic distance and connectivity maps for segmented areas and is publicly available.

AB - In this work we demonstrate how Finsler geometry---and specifically the related geodesic tracto-graphy---can be levied to analyze structural connections between different brain regions. We present new theoretical developments which support the definition of a novel Finsler metric and associated connectivity measures, based on closely related works on the Riemannian framework for diffusion MRI. Using data from the Human Connectome Project, as well as population data from an autism spectrum disorder study, we demonstrate that this new Finsler metric, together with the new connectivity measures, results in connectivity maps that are much closer to known tract anatomy compared to previous geodesic connectivity methods. Our implementation can be used to compute geodesic distance and connectivity maps for segmented areas and is publicly available.

KW - Connectivity analysis

KW - Diffusion MRI

KW - Finsler geometry

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DO - 10.1137/18M1209428

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EP - 575

JO - SIAM Journal on Imaging Sciences

JF - SIAM Journal on Imaging Sciences

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Structural connectivity analysis using finsler geometry

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