Bi-exponential magnetic resonance signal model for partial volume computation.

Quentin Duché 1, 2, 3 Oscar Acosta 1 Giulio Gambarota 1, 3 Isabelle Merlet 1 Olivier Salvado 2 Hervé Saint-Jalmes 1, 3, 4, *
* Auteur correspondant
1 LTSI - Laboratoire Traitement du Signal et de l'Image
2 Preventative Health National Research Flagship
3 PRISM - Plate-forme Rennaise d'Imagerie et Spectroscopie Structurale et Métabolique
4 CRLCC - CRLCC Eugène Marquis
Abstract : Accurate quantification of small structures in magnetic resonance (MR) images is often limited by partial volume (PV) effects which arise when more than one tissue type is present in a voxel. PV may be critical when dealing with changes in brain anatomy as the considered structures such as gray matter (GM) are of similar size as the MR spatial resolution. To overcome the limitations imposed by PV effects and achieve subvoxel accuracy different methods have been proposed. Here, we describe a method to compute PV by modeling the MR signal with a biexponential linear combination representing the contribution of at most two tissues in each voxel. In a first step, we estimated the parameters (T1, T2 and proton density) per tissue. Then, based on the bi-exponential formulation one can retrieve fractional contents by solving a linear system of two equations with two unknowns, namely tissue magnetizations. Preliminary tests were conducted on images acquired on a specially designed physical phantom for the study of PV effects. Further, the model was tested on BrainWeb simulated brain images to estimate GM and white matter (WM) PV effects. Root mean squared error was computed between the BrainWeb ground truth and the obtained GM and WM PV maps. The proposed method outperformed traditionally used methods by 33% and 34% in GM and WM, respectively.
keyword : Bi-exponential model MR Signal partial volume correction
Type de document :
Article dans une revue
Med Image Comput Comput Assist Interv, Springer, 2012, 15 (Pt 1), pp.231-8
Liste complète des métadonnées

Littérature citée [9 références]  Voir  Masquer  Télécharger
http://www.hal.inserm.fr/inserm-00773263
Contributeur : Lotfi Senhadji <>
Soumis le : mardi 15 janvier 2013 - 20:57:07
Dernière modification le : mercredi 16 mai 2018 - 11:24:04
Document(s) archivé(s) le : mardi 16 avril 2013 - 03:52:20

Fichiers

inserm-00773263_edited.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : inserm-00773263, version 1
  • PUBMED : 23285556

Collections

FNCLCC | MARQUIS | IRSTEA | LTSI | BIOSIT | INRA | UNIV-RENNES

Citation

Quentin Duché, Oscar Acosta, Giulio Gambarota, Isabelle Merlet, Olivier Salvado, et al.. Bi-exponential magnetic resonance signal model for partial volume computation.. Med Image Comput Comput Assist Interv, Springer, 2012, 15 (Pt 1), pp.231-8. 〈inserm-00773263〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

1466

Téléchargements de fichiers

651

Contact

support.ccsd.cnrs.fr
hal.support@ccsd.cnrs.fr
Logo CCSD