Fiche publication
Date publication
janvier 2009
Journal
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Auteurs
Membres identifiés du Cancéropôle Est :
Pr HEITZ Fabrice
,
Dr NOBLET Vincent
Tous les auteurs :
Sharma S, Noblet V, Rousseau F, Heitz F, Rumbach L, Armspach JP
Lien Pubmed
Résumé
In this paper, we study the performance of popular brain atrophy estimation algorithms using a simulated gold standard. The availability of a gold standard facilitates a sound evaluation of the measures of atrophy estimation, which is otherwise complicated. Firstly, we propose an approach for the construction of a gold standard. It involves the simulation of a realistic brain tissue loss based on the estimation of a topology preserving B-spline based deformation fields. Using this gold standard, we present an evaluation of three standard brain atrophy estimation methods (SIENA, SIENAX and BSI) in the presence of bias field inhomogeneity and noise. The effect of brain lesion load on the measured atrophy is also evaluated. Our experiments demonstrate that SIENA, SIENAX and BSI show a deterioration in their performance in the presence of bias field inhomogeneity and noise. The observed mean absolute errors in the measured Percentage of Brain Volume Change (PBVC) are 0.35% +/- 0.38, 2.03% +/- 1.46 and 0.91% +/- 0.80 for SIENA, SIENAX and BSI, respectively, for simulated whole brain atrophies in the range 0-1%.
Mots clés
Algorithms, Atrophy, pathology, Brain, pathology, Computer Simulation, Humans, Image Enhancement, methods, Image Interpretation, Computer-Assisted, methods, Models, Neurological, Pattern Recognition, Automated, methods, Reproducibility of Results, Sensitivity and Specificity, Subtraction Technique
Référence
Med Image Comput Comput Assist Interv. 2009 ;12(Pt 2):566-74
