Dense deformation field estimation for atlas-based segmentation of pathological MR brain images.

Détails

ID Serval
serval:BIB_8195F4304A64
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Dense deformation field estimation for atlas-based segmentation of pathological MR brain images.
Périodique
Computer Methods and Programs in Biomedicine
Auteur(s)
Bach Cuadra M., De Craene M., Duay V., Macq B., Pollo C., Thiran J.P.
ISSN
0169-2607 (Print)
ISSN-L
0169-2607
Statut éditorial
Publié
Date de publication
2006
Volume
84
Numéro
2-3
Pages
66-75
Langue
anglais
Notes
Publication types: Research Support, Non-U.S. Gov't ; Validation StudiesPublication Status: ppublish
Résumé
Atlas registration is a recognized paradigm for the automatic segmentation of normal MR brain images. Unfortunately, atlas-based segmentation has been of limited use in presence of large space-occupying lesions. In fact, brain deformations induced by such lesions are added to normal anatomical variability and they may dramatically shift and deform anatomically or functionally important brain structures. In this work, we chose to focus on the problem of inter-subject registration of MR images with large tumors, inducing a significant shift of surrounding anatomical structures. First, a brief survey of the existing methods that have been proposed to deal with this problem is presented. This introduces the discussion about the requirements and desirable properties that we consider necessary to be fulfilled by a registration method in this context: To have a dense and smooth deformation field and a model of lesion growth, to model different deformability for some structures, to introduce more prior knowledge, and to use voxel-based features with a similarity measure robust to intensity differences. In a second part of this work, we propose a new approach that overcomes some of the main limitations of the existing techniques while complying with most of the desired requirements above. Our algorithm combines the mathematical framework for computing a variational flow proposed by Hermosillo et al. [G. Hermosillo, C. Chefd'Hotel, O. Faugeras, A variational approach to multi-modal image matching, Tech. Rep., INRIA (February 2001).] with the radial lesion growth pattern presented by Bach et al. [M. Bach Cuadra, C. Pollo, A. Bardera, O. Cuisenaire, J.-G. Villemure, J.-Ph. Thiran, Atlas-based segmentation of pathological MR brain images using a model of lesion growth, IEEE Trans. Med. Imag. 23 (10) (2004) 1301-1314.]. Results on patients with a meningioma are visually assessed and compared to those obtained with the most similar method from the state-of-the-art.
Mots-clé
Brain/pathology, Humans, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging
Pubmed
Web of science
Création de la notice
31/08/2011 11:18
Dernière modification de la notice
03/03/2018 18:48
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