title: 3D brain segmentation using active appearance models and local regressors.
abstract: We describe an efficient and accurate method for segmenting sets of subcortical structures in 3D MR images of the brain. We first find the approximate position of all the structures using a global Active Appearance Model (AAM). We then refine the shape and position of each structure using a set of individual AAMs trained for each. Finally we produce a detailed segmentation by computing the probability that each voxel belongs to the structure, using regression functions trained for each individual voxel. The models are trained using a large set of labelled images, using a novel variant of 'groupwise' registration to obtain the necessary image correspondences. We evaluate the method on a large dataset, and demonstrate that it achieves results comparable with some of the best published.
authors.affiliation: Division of Imaging Science and Biomedical Engineering, The University of Manchester, Manchester, UK. kola.babalola@manchester.ac.uk
authors.forename: K O
authors.initials: KO
authors.lastname: Babalola
authors.forename: T F
authors.initials: TF
authors.lastname: Cootes
authors.forename: C J
authors.initials: CJ
authors.lastname: Twining
authors.forename: V
authors.initials: V
authors.lastname: Petrovic
authors.forename: C J
authors.initials: CJ
authors.lastname: Taylor
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001185:Artificial Intelligence; D001921:Brain / Q000033:anatomy & histology*; D002648:Child; D002675:Child, Preschool; D003198:Computer Simulation; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods*; D012044:Regression Analysis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity