BACKGROUND: The statistical shape atlas is a 3D medical image analysis tool that encodes shape variations between populations. However, efficiency, accuracy and finding the correct correspondence are still unsolved issues during the construction of the atlas. METHODS: We developed a two-level-based framework that speeds up the registration process while maintaining accuracy of the atlas. We also proposed a semi-automatic strategy to achieve segmentation and registration simultaneously, without knowing any prior information about the shape. RESULTS: We have separately constructed the atlas for the femur and spine. The experimental results demonstrate the efficiency and accuracy of our methods. CONCLUSIONS: Our two-level framework and semi-automatic strategy are able to efficiently construct the atlas for bone structures without losing accuracy. We can handle either 3D surface data or raw DICOM images.
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