Abstract
Tooth segmentation from dental computed tomography (CT) images with metal artifacts is challenging as metal artifacts make some of the crown boundaries unrecognizable. This letter proposes a semiautomatic method for crown segmentation from CT images with metal artifacts. A user manually selects a starting slice and initializes this slice. Then crown contours are segmented automatically from volumetric CT images slice by slice. In the segmentation of each slice, the Radon transform is used to extract a line to separate neighboring crowns into independent ones. A statistical shape prior-based level set model is then applied to segment each crown from the mesial or distal side of the line. The proposed method was tested on 15 set of volumetric images. Experimental results validated that it is effective to extract crown contours from CT images with metal artifacts.
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