Periodic Area-of-Motion characterization for Bio-Medical applications

Abstract : Many bio-medical applications involve the analysis of sequences for motion characterization. In this article, we consider 2D+t sequences where a particular motion (e.g. a blood flow) is associated with a specific area of the 2D image (e.g. an artery) but multiple motions may exist simultaneously in the same sequences (e.g. there may be several blood vessels present, each with their specific flow). The characterization of this type of motion typically involves first finding the areas where motion is present, followed by an analysis of these motions: speed, regularity, frequency, etc. In this article, we propose a methodology called " area-of-motion characterization " suitable for simultaneously detecting and characterizing areas where motion is present in a sequence. We can then classify this motion into consistent areas using unsupervised learning and produce directly usable metrics for various applications. We illustrate this methodology for the analysis of cilia motion on ex-vivo human samples, and we apply and validate the same methodology for blood flow analysis in fish embryo.
Type de document :
Communication dans un congrès
ISBI 2017, Apr 2017, Melbourne, Australia
Liste complète des métadonnées

Littérature citée [13 références]  Voir  Masquer  Télécharger

https://hal.archives-ouvertes.fr/hal-01467878
Contributeur : Elodie Puybareau <>
Soumis le : mardi 14 février 2017 - 18:09:47
Dernière modification le : samedi 3 juin 2017 - 16:38:16

Fichier

article_ISBI2017.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-01467878, version 1

Collections

Citation

Élodie Puybareau, Hugues Talbot, Laurent Najman. Periodic Area-of-Motion characterization for Bio-Medical applications. ISBI 2017, Apr 2017, Melbourne, Australia. 〈hal-01467878〉

Partager

Métriques

Consultations de la notice

103

Téléchargements de fichiers

33