X-Ray Analysis

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Computer Aided Dental X-Rays Analysis Using Automatic Gaussian Fitting Energy And Level Sets
Anupama Bhan, Malay Kishore Dutta, Pulkit Pandey
Department of Electronics and Communication Engineering
Amity University, Noida, India Abstract--Identification of the Root canal length is a major concern in the dentistry worldwide, which currently seeks the manual calculation in order to detect the measurement of the teeth. This method presents an algorithm for fast and automatic measurement of the teeth prior to root canal therapy and molar endodontics. Intensity inhomogeneity often is a major problem in dental x-rays which causes considerable difficulties in segmentation. This method provides a combinational approach of Local Gaussian Distribution
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Research shows that ninety percent of people irrespective of the age and gender are suffering from dental problems. Various types of images are used in dentistry for correct diagnosis and treatment planning for example X-rays [1], dental radiographs, etc. The most common X-rays used are the intraoral, depending upon whether the X-ray film is inside or outside the mouth and are classified by either beitwing X-ray, periapical X-ray or panoramic X-rays. Beitwing X-rays have some advantages over the other imaging techniques as the lesions are more prominent in beitwing radiographs…show more content…
Now the application of Local Gaussian deistribution fitting energy with level sets is an easy task. Now it’s applied to the image so as to detect the measure.

Now the measure are calculated from this image. Table I shows the values of the different parameters for different types of periapical dental X-rays.
Table I
Based on the application of the algorithm, the different lengths of root canal and other measures are calculated from the teeth. Table II shows the results of some test set images.
Table II
By the implementation, the above mentioned technique gives accurate measure of teeth with very less time complexity.

IV. CONCLUSION
In this paper, a novel approach is proposed to detect the measure of the teeth from dental x-ray images. The top hat-bottom hat transformation is followed by smoothening of the image to enhance the contrast and the boundaries of the image respectively. The statistics of the teeth are calculated so as to provide the dentists with an accurate and faster method of the detection of the measure of the teeth. The work has given appreciable results and can be aimed for coloured dental

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