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We present a novel image segmentation method based on statistical shape model fitting. Instead of fitting the model to raw intensity values we consider object probabilities. The abstraction from the plain intensity images to probability maps makes the segmentation more robust against misleading texture inside the object or surrounding background. The target object probability is predicted based on...
The fundamental step to get a Statistical Shape Model (SSM) is to align all the training samples to the same spatial modality. In this paper, we propose a new 3D alignment method using surface parameterization theory to solve the rotation transformation of 3D rigid registration. It is a feature based alignment method which matches two models depending on comparing the distribution of spherical conformal...
Since the medical training samples are very limited, it is difficult to construct a statistical shape model with good generalization using few samples. In this paper, we propose a novel statistical shape modeling method using 2D PCA. The 3D shape is represented as a matrix by spherical parameterization. The experiments showed that our proposed method can reconstruct statistical shape model with good...
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