Automated identification of brain tumors from single MR images based on segmentation with refined patient-specific priors

Abstract : Brain tumors can have different shapes or locations, making their identification very challenging. In functional MRI, it is not unusual that patients have only one anatomical image due to time and financial constraints. Here, we provide a modified automatic lesion identification (ALI) procedure which enables brain tumor identification from single MR images. Our method rests on (A) a modified segmentation-normalization procedure with an explicit " extra prior " for the tumor and (B) an outlier detection procedure for abnormal voxel (i.e., tumor) classification. To minimize tissue misclassification, the segmentation-normalization procedure requires prior information of the tumor location and extent. We therefore propose that ALI is run iteratively so that the output of Step B is used as a patient-specific prior in Step A. We test this procedure on real T1-weighted images from 18 patients, and the results were validated in comparison to two independent observers' manual tracings. The automated procedure identified the tumors successfully with an excellent agreement with the manual segmentation (area under the ROC curve = 0.97 ± 0.03). The proposed procedure increases the flexibility and robustness of the ALI tool and will be particularly useful for lesion-behavior mapping studies, or when lesion identification and/or spatial normalization are problematic.
Type de document :
Article dans une revue
Frontiers in Neuroscience, Frontiers, 2013, 7, pp.241. 〈10.3389/fnins.2013.00241〉
Liste complète des métadonnées

Littérature citée [55 références]  Voir  Masquer  Télécharger

http://hal.upmc.fr/hal-01578520
Contributeur : Gestionnaire Hal-Upmc <>
Soumis le : mardi 29 août 2017 - 13:28:09
Dernière modification le : jeudi 11 janvier 2018 - 06:25:43

Fichier

fnins-07-00241.pdf
Publication financée par une institution

Licence


Distributed under a Creative Commons Paternité 4.0 International License

Identifiants

Collections

UPMC | ICM

Citation

Ana Sanjuán, Cathy J. Price, Laura Mancini, Goulven Josse, Alice Grogan, et al.. Automated identification of brain tumors from single MR images based on segmentation with refined patient-specific priors. Frontiers in Neuroscience, Frontiers, 2013, 7, pp.241. 〈10.3389/fnins.2013.00241〉. 〈hal-01578520〉

Partager

Métriques

Consultations de la notice

59

Téléchargements de fichiers

21