Construction and validation of mean shape atlas templates for atlas-based brain image segmentation.
In this paper, we evaluate different schemes for constructing a mean shape anatomical atlas for atlas-based segmentation of MR brain images. Each atlas is constructed and validated using a database of 20 images for which detailed manual delineations of 49 different subcortical structures are available. Atlas construction and atlas based segmentation are performed by non-rigid intensity-based registration using a viscous fluid deformation model with parameters that were optimally tuned for this particular task. The segmentation performance of each atlas scheme is evaluated on the same database using a leave-one-out approach and measured by the volume overlap of corresponding regions in the ground-truth manual segmentation and the warped atlas label image.
Wang
Qian
Q
Katholieke Universiteit Leuven, Faculties of Medicine and Engineering, Medical Image Computing - ESAT/PSI, University Hospital Gasthuisberg, Herestraat 49, B-3000 Leuven, Belgium. Qian.Wang@uz.kuleuven.ac.be
Seghers
Dieter
D
D'Agostino
Emiliano
E
Maes
Frederik
F
Vandermeulen
Dirk
D
Suetens
Paul
P
Hammers
Alexander
A
D000328:Adult; D000465:Algorithms; D000716:Anatomy, Artistic / Q000379:methods; D001185:Artificial Intelligence; D001921:Brain / Q000033:anatomy & histology*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008488:Medical Illustration; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique