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| The Study of Extraction Methods of Dental Three-Dimensional Features Based on Improved Discrete Curve Evolution |
1 School of Life Science and Technology, University of Electronic Science and Technology, Chengdu 610054, China
2 College of Electronic Engineering, Chengdu University of Information Technology, Chengdu 610225, China
3 College of Network Engineering, Chengdu University of Information Technology, Chengdu 610225, China |
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Abstract Extraction of tooth feature points effectively is of significance for the subsequent three-dimensional registration and reconstruction. However, the efficiency of current calculation methods is low. This work improved discrete curve evolution (DCE) algorithm and used characteristic factor of curve (CFOC) to describe the complexity of contour on each dental CT slice. With the adaptive CFOC, the feature points number in curves in different slices could be determined, thus the redundancy in the stored data was reduced, improving the extraction efficiency of feature points. The improved DCE algorithm was used for exacting the feature points from different clinical CT slices, comparing experimental results with that of the conventional DCE algorithm. The results showed that the improved method saved nearly half of time that the conventional method required for extracting feature points from each CT slice, and the feature points number extracted by the improved method is approximately four fifths of that of the conventional method. After cubic spline interpolation with different ratios of the feature points from different slices, the slice images were reconstructed and the reconstruction results reflected the true structure of the teeth. Therefore, the calculation efficiency of the improved method is much higher than that of the conventional DCE algorithm.
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