Teeth Segmentation of Bitewing X-Ray Images Using Wavelet Transform

Sina Salimzadeh, Sara Kandulu


Within the recent twenty years, the dental X-ray images have widely been employed in forensic odontology for human identification, particularly where mass disasters happen. In this paper, a novel method is proposed for the process of teeth segmentation and individual teeth isolation of Bitewing X-ray radiographs. The main objective of this study is to develop an automatic teeth segmentation approach that can be used in an Automated Dental Identification System (ADIS).

The proposed method is based on separating teeth according to edge lines between crowns of teeth. It comprises four phases as image enhancement, edge detection by using wavelet transform, Region of Interest (ROI) definition, and morphological processing. Image enhancement in our case is done by image sharpening using a Butterworth high pass filter. Directional changes of the image and a blurred version of it are obtained by wavelet transform in the second phase. In ROI definition the upper and lower jaws are first separated using the integral intensity projection and then a region containing the desired edge lines are defined. In the final stage, some morphological operations are applied to isolate the teeth based on separating edge lines.

The evaluation of the teeth segmentation is measured by isolating accuracy and visual inspection. Experimental results with 90.6% isolation accuracy of total 681 teeth illustrate that the proposed method is more efficient that the existing algorithms.

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DOI: https://doi.org/10.31449/inf.v44i4.2774

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