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A Novel White Matter Fibre Tracking Algorithm Using Probabilistic Tractography and Average Curves

Ratnarajah, Nagulan and Simmons, Andy and Davydov, Oleg and Hojjatoleslami, Ali (2010) A Novel White Matter Fibre Tracking Algorithm Using Probabilistic Tractography and Average Curves. In: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2010 13th International Conference. Lecture Notes in Computer Science . Springer, Berlin, Germany, pp. 666-673. ISBN 978-3-642-15704-2. E-ISBN 978-3-642-15705-9. (doi:10.1007/978-3-642-15705-9_81) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:27603)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
http://dx.doi.org/10.1007/978-3-642-15705-9_81

Abstract

This paper presents a novel white matter fibre tractography approach using average curves of probabilistic fibre tracking measures. We compute ”representative” curves from the original probabilistic curve-set using two different averaging methods. These typical curves overcome a number of the limitations of deterministic and probabilistic approaches. They produce strong connections to every anatomically distinct fibre tract from a seed point and also convey important information about the underlying probability distribution. A new clustering algorithm is employed to separate fibres into branches before applying averaging methods. The performance of the technique is verified on a wide range of seed points using a phantom dataset and an in vivo dataset.

Item Type: Book section
DOI/Identification number: 10.1007/978-3-642-15705-9_81
Subjects: Q Science > QA Mathematics (inc Computing science) > QA299 Analysis, Calculus
Q Science > QA Mathematics (inc Computing science) > QA440 Geometry > QA611 Topology
Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming, > QA76.76.E95 Expert Systems (Intelligent Knowledge Based Systems)
Q Science > QA Mathematics (inc Computing science) > QA564 Algebraic Geometry
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science
Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: S.A. Hojjatoleslami
Date Deposited: 19 May 2011 10:57 UTC
Last Modified: 16 Nov 2021 10:05 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/27603 (The current URI for this page, for reference purposes)

University of Kent Author Information

Ratnarajah, Nagulan.

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Hojjatoleslami, Ali.

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