A Study on Automatic Tooth Root Segmentation For Dental CT Images

Abstract

Dentist can obtain 3D anatomical information without distortion and information loss by using dental Computed Tomography scan images on line, and also can make the preoperative plan of implant placement or orthodontics. It is essential to segment individual tooth for making an accurate diagnosis. However, it is very difficult to distinguish the difference in the brightness between the dental and adjacent area. Especially, the root of a tooth is very elusive to automatically identify in dental CT images because jawbone normally adjoins the tooth. In the paper, we propose a method of automatically tooth region segmentation, which can identify the root of a tooth clearly. This algorithm separate the tooth from dental CT scan images by using Seeded Region Growing method on dental crown and by using Level-set method on dental root respectively. By using the proposed method, the results can be acquired average 19.2% better accuracy, compared to the result of the previous methods.

Mask-Transformer-Based Networks for Teeth Segmentation in Panoramic Radiographs

“…In a similar vein, Chandran et al [33] improved the quality of dental images by applying CLAHE, followed by the Otsu threshold method for teeth segmentation. Level set methods have been utilized by studies [34,35] to enhance the root contrast, thus improving segmentation. Horizontal and vertical integral projection methods have also been deployed, although their performance was not satisfactory [36,37].…”