【摘 要】
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A learning-based deformable registration method was presented for MR brain images. First, best geometric features are selected for each location and each resolu
【机 构】
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Dept. of Computer Science and Eng.
论文部分内容阅读
A learning-based deformable registration method was presented for MR brain images. First, best geometric features are selected for each location and each resolution, in order to reduce ambiguity in matching during image registration. The best features are obtained by solving an energy minimization problem, which requires the features to be distinctive around the neighboring points and consistency across training samples. Secondly, the set of active points is hierarchically selected based on their saliency and consistency measurements during registration,which helps to produce accurate registration results. Finally, by incorporating those learned results into the framework of HAMMER, great improvement in both real data and simulated data is achieved.
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