Multi-Compartment T2 Relaxometry Model Using Gamma Distribution Representations: A Framework for Quantitative Estimation of Brain Tissue Microstructures

Sudhanya Chatterjee 1 Olivier Commowick 1 Simon K. Warfield 2 Christian Barillot 1
1 VisAGeS - Vision, Action et Gestion d'informations en Santé
INSERM - Institut National de la Santé et de la Recherche Médicale : U1228, Inria Rennes – Bretagne Atlantique , IRISA_D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
2 CRL - Computational Radiology Laboratory [Boston]
Abstract : Advanced MRI techniques (e.g. – d-MRI, MT, relaxometry etc.) can provide quantitative information of brain tissues. Image voxels are often heterogeneous in terms of microstructure information due to physical limitations and imaging resolution. Quantitative assessment of the brain tissue microstructure can provide valuable insights into neurodegenerative diseases (e.g. - Multiple Sclerosis). In this work, we propose a multicompartment model for T2-Relaxometry to obtain brain microstructure information in a quantitative framework. The proposed method allows simultaneous estimation of the model parameters.
Keywords : Relaxometry MRI Multi-compartment model
Type de document :
Communication dans un congrès
ISMRM 25TH ANNUAL MEETING & EXHIBITION, Apr 2017, Honolulu, Hawaii, USA, United States
Liste complète des métadonnées
https://www.hal.inserm.fr/inserm-01543073
Contributeur : Sudhanya Chatterjee <>
Soumis le : mardi 20 juin 2017 - 14:39:41
Dernière modification le : jeudi 14 février 2019 - 08:28:02

Identifiants

  • HAL Id : inserm-01543073, version 1

Collections

INRIA | IRISA | INRIA2017 | UR1-UFR-ISTIC | UNIV-RENNES

Citation

Sudhanya Chatterjee, Olivier Commowick, Simon K. Warfield, Christian Barillot. Multi-Compartment T2 Relaxometry Model Using Gamma Distribution Representations: A Framework for Quantitative Estimation of Brain Tissue Microstructures. ISMRM 25TH ANNUAL MEETING & EXHIBITION, Apr 2017, Honolulu, Hawaii, USA, United States. 〈inserm-01543073〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

301

Contact

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