Adaptive pixon represented segmentation (APRS) for 3D MR brain images based on mean shift and Markov random fields

Lei Lin 1, 2, 3 Daniel Garcia-Lorenzo 3 Chong Li 1, 4 Jiang Tianzi 5 Christian Barillot 3, *
* Auteur correspondant
3 VisAGeS - Vision, Action et Gestion d'informations en Santé
INSERM - Institut National de la Santé et de la Recherche Médicale : U746, Inria Rennes – Bretagne Atlantique , IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
Abstract : In this paper, we proposed an adaptive pixon represented segmentation (APRS) algorithm for 3D magnetic resonance (MR) brain images. Different from traditional method, an adaptive mean shift algorithm was adopted to adaptively smooth the query image and create a pixon-based image representation. Then K-means algorithm was employed to provide an initial segmentation by classifying the pixons in image into a predefined number of tissue classes. By using this segmentation as initialization, expectation-maximization (EM) iterations composed of bias correction, a priori digital brain atlas information, and Markov random field (MRF) segmentation were processed. Pixons were assigned with final labels when the algorithm converges. The adoption of bias correction and brain atlas made the current method more suitable for brain image segmentation than the previous pixon based segmentation algorithm. The proposed method was validated on both simulated normal brain images from BrainWeb and real brain images from the IBSR public dataset. Compared with some other popular MRI segmentation methods, the proposed method exhibited a higher degree of accuracy in segmenting both simulated and real 3D MRI brain data. The experimental results were numerically assessed using Dice and Tanimoto coefficients.
Type de document :
Article dans une revue
Pattern Recognition Letters, Elsevier, 2011, 32 (7), pp.1036-1043. 〈10.1016/j.patrec.2011.02.016〉
Liste complète des métadonnées

Littérature citée [50 références]  Voir  Masquer  Télécharger

https://www.hal.inserm.fr/inserm-00723811
Contributeur : Christian Barillot <>
Soumis le : mardi 14 août 2012 - 12:26:18
Dernière modification le : jeudi 15 novembre 2018 - 11:57:30
Document(s) archivé(s) le : vendredi 16 décembre 2016 - 06:05:16

Fichier

 Accès restreint
Fichier visible le : jamais

Connectez-vous pour demander l'accès au fichier

Identifiants

Citation

Lei Lin, Daniel Garcia-Lorenzo, Chong Li, Jiang Tianzi, Christian Barillot. Adaptive pixon represented segmentation (APRS) for 3D MR brain images based on mean shift and Markov random fields. Pattern Recognition Letters, Elsevier, 2011, 32 (7), pp.1036-1043. 〈10.1016/j.patrec.2011.02.016〉. 〈inserm-00723811〉

Partager

Métriques

Consultations de la notice

272