Estimating A Reference Standard Segmentation with Spatially Varying Performance Parameters: Local MAP STAPLE

Olivier Commowick 1, 2, * Alireza Akhondi-Asl 2 Simon K. Warfield 2
* Auteur correspondant
1 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 : We present a new algorithm, called local MAP STAPLE, to estimate from a set of multi-label segmentations both a reference standard segmentation and spatially varying performance parameters. It is based on a sliding window technique to estimate the segmentation and the segmentation performance parameters for each input segmentation. In order to allow for optimal fusion from the small amount of data in each local region, and to account for the possibility of labels not being observed in a local region of some (or all) input segmentations, we introduce prior probabilities for the local performance parameters through a new Maximum A Posteriori formulation of STAPLE. Further, we propose an expression to compute confidence intervals in the estimated local performance parameters. We carried out several experiments with local MAP STAPLE to characterize its performance and value for local segmentation evaluation. First, with simulated segmentations with known reference standard segmentation and spatially varying performance, we show that local MAP STAPLE performs better than both STAPLE and majority voting. Then we present evaluations with data sets from clinical applications. These experiments demonstrate that spatial adaptivity in segmentation performance is an important property to capture. We compared the local MAP STAPLE segmentations to STAPLE, and to previously published fusion techniques and demonstrate the superiority of local MAP STAPLE over other state-ofthe- art algorithms.
Type de document :
Article dans une revue
IEEE Transactions on Medical Imaging, Institute of Electrical and Electronics Engineers, 2012, 31 (8), pp.1593-1606. 〈10.1109/TMI.2012.2197406〉
Liste complète des métadonnées

Littérature citée [26 références]  Voir  Masquer  Télécharger

http://www.hal.inserm.fr/inserm-00697775
Contributeur : Olivier Commowick <>
Soumis le : mercredi 16 mai 2012 - 11:12:24
Dernière modification le : mercredi 2 août 2017 - 10:10:52
Document(s) archivé(s) le : vendredi 17 août 2012 - 02:25:18

Fichiers

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

Identifiants

Citation

Olivier Commowick, Alireza Akhondi-Asl, Simon K. Warfield. Estimating A Reference Standard Segmentation with Spatially Varying Performance Parameters: Local MAP STAPLE. IEEE Transactions on Medical Imaging, Institute of Electrical and Electronics Engineers, 2012, 31 (8), pp.1593-1606. 〈10.1109/TMI.2012.2197406〉. 〈inserm-00697775〉

Partager

Métriques

Consultations de
la notice

464

Téléchargements du document

500