Multimodal evaluation for medical image segmentation

Détails

ID Serval
serval:BIB_427D132FE642
Type
Actes de conférence (partie): contribution originale à la littérature scientifique, publiée à l'occasion de conférences scientifiques, dans un ouvrage de compte-rendu (proceedings), ou dans l'édition spéciale d'un journal reconnu (conference proceedings).
Collection
Publications
Titre
Multimodal evaluation for medical image segmentation
Titre de la conférence
12th International Conference on Computer Analysis of Images and Patterns
Auteur(s)
Cardenes R., Bach M., Chi Y., Marras I., de Luis R., Anderson M., Cashman P., Bultelle M.
Adresse
Vienna, Austria, August 27-29, 2007
ISBN
0302-9743
Statut éditorial
Publié
Date de publication
2007
Peer-reviewed
Oui
Volume
4673
Série
Lecture Notes in Computer Science
Pages
229-236
Langue
anglais
Notes
Publication type : Proceedings Paper
Résumé
This paper is a joint effort between five institutionsthat introduces several novel similarity measures andcombines them to carry out a multimodal segmentationevaluation. The new similarity measures proposed arebased on the location and the intensity values of themisclassified voxels as well as on the connectivity andthe boundaries of the segmented data. We showexperimentally that the combination of these measuresimprove the quality of the evaluation. The study that weshow here has been carried out using four differentsegmentation methods from four different labs applied toa MRI simulated dataset of the brain. We claim that ournew measures improve the robustness of the evaluation andprovides better understanding about the differencebetween segmentation methods.
Mots-clé
Multimodal evaluation, segmentation, similarity measures, brain tissue segmentation,
Création de la notice
29/11/2011 17:40
Dernière modification de la notice
03/03/2018 16:38
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