title: Automatic construction of statistical shape models for vertebrae.
abstract: For segmenting complex structures like vertebrae, a priori knowledge by means of statistical shape models (SSMs) is often incorporated. One of the main challenges using SSMs is the solution of the correspondence problem. In this work we present a generic automated approach for solving the correspondence problem for vertebrae. We determine two closed loops on a reference shape and propagate them consistently to the remaining shapes of the training set. Then every shape is cut along these loops and parameterized to a rectangle. There, we optimize a novel combined energy to establish the correspondences and to reduce the unavoidable area and angle distortion. Finally, we present an adaptive resampling method to achieve a good shape representation. A qualitative and quantitative evaluation shows that using our method we can generate SSMs of higher quality than the ICP approach.
authors: GRIS, TU Darmstadt, Fraunhoferstrasse 5, 64287 Darmstadt, Germany. meike.becker@gris.tu-darmstadt.de
authors: Meike
authors: M
authors: Becker
authors: Matthias
authors: M
authors: Kirschner
authors: Simon
authors: S
authors: Fuhrmann
authors: Stefan
authors: S
authors: Wesarg
mesh_terms: D000465:Algorithms; D001331:Automation; D003198:Computer Simulation; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008159:Lumbar Vertebrae / Q000033:anatomy & histology / Q000473:pathology*; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods; D012016:Reference Values; D015203:Reproducibility of Results