A novel white matter fibre tracking algorithm using probabilistic tractography and average curves

Nagulan Ratnarajah, Andrew Simmons, Oleg Davydov, Ali Hojjatoleslami

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

4 Citations (Scopus)

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.
Original languageEnglish
Title of host publicationMedical Image Computing and Computer-Assisted Intervention – MICCAI 2010
Subtitle of host publication13th International Conference, Beijing, China, September 20-24, 2010, Proceedings, Part I
Place of PublicationHeidelberg
PublisherSpringer
Pages666-73
Number of pages8
Volume6361
ISBN (Electronic)978-3-642-15705-9
ISBN (Print)978-3-642-15704-2
DOIs
Publication statusPublished - 2010

Publication series

NameLecture Notes in Computer Science
Volume6361
ISSN (Print)0302-9743

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