title: Use of simulated atrophy for performance analysis of brain atrophy estimation approaches.
abstract: 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%.
authors.affiliation: LINC-IPB (UMR CNRS-UDS 7191), Strasbourg, France. swati.sharma@linc.u-strasbg.fr
authors.forename: Swati
authors.initials: S
authors.lastname: Sharma
authors.forename: Vincent
authors.initials: V
authors.lastname: Noblet
authors.forename: François
authors.initials: F
authors.lastname: Rousseau
authors.forename: Fabrice
authors.initials: F
authors.lastname: Heitz
authors.forename: Lucien
authors.initials: L
authors.lastname: Rumbach
authors.forename: Jean-Paul
authors.initials: JP
authors.lastname: Armspach
mesh_terms: D000465:Algorithms; D001284:Atrophy / Q000473:pathology; D001921:Brain / Q000473:pathology*; D003198:Computer Simulation; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008959:Models, Neurological; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique