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Procrustes analysis of muscle fascicle shapes based on DTI fibre tracking

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conference contribution
posted on 2022-08-02, 09:49 authored by Lei Ye, Eugenie Hunsicker, Baihua LiBaihua Li, Diwei ZhouDiwei Zhou

Diffusion Tensor Imaging (DTI) is a technique developed from Magnetic Resonance Imaging (MRI), which uses a mathematical form diffusion tensor to measure the movement of water molecules in biological tissues in vivo. By performing fibre tracking using diffusion tensor data, we can study the micro-structure of biological tissues in a non-invasive way. Skeletal muscle plays a significant role in force and power generation that contribute to maintaining body postures and to controlling its movements. DTI fibre tracking may re-construct the skeletal muscle in a fascicle level. Procrustes analysis is a landmark-based method for studying the shapes of objects. In this paper, we explore using Generalised Procrustes Analysis to study the fascicle shapes that we have collected in medial gastrocnemius muscles from 6 healthy adults by using DTI technology. This is an innovated attempt of using Procrustes analysis to find the trend of the changes of fascicle shape when foot is in plantarflexion and dorsiflexion, by clustering method. 

History

School

  • Science

Department

  • Mathematical Sciences
  • Computer Science

Published in

Medical Image Understanding and Analysis: 26th Annual Conference, MIUA 2022, Cambridge, UK, July 27–29, 2022, Proceedings

Pages

172-186

Source

Annual Conference on Medical Image Understanding and Analysis (MIUA 2022)

Publisher

Springer

Version

  • AM (Accepted Manuscript)

Rights holder

© The Author(s)

Publisher statement

This version of the contribution has been accepted for publication, after peer review (when applicable) but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/978-3-031-12053-4_13. Use of this Accepted Version is subject to the publisher’s Accepted Manuscript terms of use https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms

Acceptance date

2022-07-09

Publication date

2022-07-25

Copyright date

2022

ISBN

978-3-031-12052-7; 978-3-031-12053-4

ISSN

0302-9743

eISSN

1611-3349

Book series

Lecture Notes in Computer Science (LNCS, volume 13413)

Language

  • en

Editor(s)

Guang Yang; Angelica Aviles-Rivero; Michael Roberts; Carola-Bibiane Schönlieb

Location

Cambridge, United Kingdom

Event dates

27 July 2022 - 29 July 2022

Depositor

Dr Diwei Zhou. Deposit date: 1 August 2022

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