Literature DB >> 20426205

An interactive geometric technique for upper and lower teeth segmentation.

Binh Huy Le1, Zhigang Deng, James Xia, Yu-Bing Chang, Xiaobo Zhou.   

Abstract

Due to the complexity of the dental models in semantics of both shape and form, a fully automated method for the separation of the lower and upper teeth is unsuitable while manual segmentation requires painstakingly user interventions. In this paper, we present a novel interactive method to segment the upper and lower teeth. The process is performed on 3D triangular mesh of the skull and consists of four main steps: reconstruction of 3D model from teeth CT images, curvature estimation, interactive segmentation path planning using the shortest path finding algorithm, and performing actual geometric cut on 3D models using a graph cut algorithm. The accuracy and efficiency of our method were experimentally validated via comparisons with ground truth (manual segmentation) as well as the state of art interactive mesh segmentation algorithms. We show the presented scheme can dramatically save manual effort for users while retaining an acceptable quality (with an averaged 0.29 mm discrepancy from the ideal segmentation).

Mesh:

Year:  2009        PMID: 20426205     DOI: 10.1007/978-3-642-04271-3_117

Source DB:  PubMed          Journal:  Med Image Comput Comput Assist Interv


  2 in total

1.  Automated segmentation of dental CBCT image with prior-guided sequential random forests.

Authors:  Li Wang; Yaozong Gao; Feng Shi; Gang Li; Ken-Chung Chen; Zhen Tang; James J Xia; Dinggang Shen
Journal:  Med Phys       Date:  2016-01       Impact factor: 4.071

2.  Automated segmentation of CBCT image using spiral CT atlases and convex optimization.

Authors:  Li Wang; Ken Chung Chen; Feng Shi; Shu Liao; Gang Li; Yaozong Gao; Steve G F Shen; Jin Yan; Philip K M Lee; Ben Chow; Nancy X Liu; James J Xia; Dinggang Shen
Journal:  Med Image Comput Comput Assist Interv       Date:  2013
  2 in total

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