The quantification of percentage filling of gutta-percha in obturated root canal using image processing and analysis.

Aim: To quantify the percentage filling of the gutta-percha in obturated root canal cavity using image processing and analysis.

Methodology: The image processing and analysis using the X-ray radiographs is commonly being used by medical practitioners for easy and speedy diagnosis of patient health. But these methods are qualitative and assessment depends upon dentist's own experience and perception. Fifteen patients were randomly assigned to fifteen Dentists to perform the root canal treatment using warm vertical condensation. X-ray radiographs of pre and post obturation were obtained to carry image processing and analysis. Image enhancement, low pass filtering, k-means clustering algorithm and edge detection technique were applied to get results. Percentage filling of the obturated root canal using X-ray radiography (Dentist's prediction) and proposed algorithm results of the present study were compared. Out of fifteen Dentists, the prediction of twelve Dentists were close in range of percentage filling quantified using proposed algorithm of the present study. When investigated it was found that three discrepancies found due to lack of sufficient experience of the respective Dentist. The proposed algorithm not only helps to overcome this false assessment but also helps to quantify accurate percentage filling of gutta-percha and outlines unfilled cavity gap of root canal.

Results: The proposed algorithm of present study provides accurate percentage filling of gutta-percha in the obturated root canal up to two decimal points. The present study used gutta-percha as obturation material but the study can be implemented for any obturation material.

Conclusion: The proposed algorithm of present study accurately quantified the percentage filling of root canal cavity using image processing. It also locates and outlines the unfilled root canal cavity.