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3D Brain Segmentation Using Active Appearance Models and Local Regressors
[chapter]
2008
Lecture Notes in Computer Science
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
doi:10.1007/978-3-540-85988-8_48
fatcat:eh3c6gstffdodajaqrkjnnzriu