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Journal of Applied Sciences
  Year: 2009 | Volume: 9 | Issue: 11 | Page No.: 2031-2044
DOI: 10.3923/jas.2009.2031.2044
 
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Rapid Automatic Segmentation and Visualization of Teeth in CT-Scan Data

H. Akhoondali, R.A. Zoroofi and G. Shirani

Abstract:
In this study, a fast automatic method is proposed for the segmentation and visualization of teeth in multi-slice CT-scan data of the head. The algorithm consists of five main procedures. In the first part, the mandible and maxilla are separated using maximum intensity projection in the y direction and a step like region separation algorithm. In the second part, the dental region is separated using maximum intensity projection in the z direction, thresholding and cropping. In the third part, the teeth are rapidly segmented using a region growing algorithm based on four thresholds which are used to distinguish between seed points, teeth and none teeth tissue. In the fourth part, the results are visualized using iso-surface extraction and surface and volume rendering. A semi-automatic method is also proposed for rapid metal artifact removal. Results on multiple datasets have shown the success of the algorithm with the dental region separation and segmentation procedure taking an average of only 2.4 sec to complete for each jaw making it at least tens of times faster than any previously proposed method.
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How to cite this article:

H. Akhoondali, R.A. Zoroofi and G. Shirani, 2009. Rapid Automatic Segmentation and Visualization of Teeth in CT-Scan Data. Journal of Applied Sciences, 9: 2031-2044.

DOI: 10.3923/jas.2009.2031.2044

URL: https://scialert.net/abstract/?doi=jas.2009.2031.2044

COMMENTS
08 July, 2014
Sharma Mayank:
Hello Sir,
I am doing my masters from IIT Madras and on same project.
I had gone through your paper on same topic and liked it, liked the approach.
But to actually implement it on matlab, can't figure it out how to approach.
Can you send me the codes for this segmentation and reconstruction, this will be great help.
09 July, 2014
H. Akhoondali:

Hello, The algorithm has been implemented using C++ not Matlab. Unfortunately, it is not possible to give the codes. Kind regards

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