Automatic Segmentation of Lower Jaw and Mandibular Bone in Digital Dental Panoramic Radiographs

Objectives: Panoramic x-ray is a medical imaging technique used in dentistry. This paper aims to present fully automatic segmentation algorithm to extract lower jaw and mandible from panoramic x-ray. Methods/Analysis: Panoramic x-rays provide features of various diseases like advanced periodontal diseases, cysts, tumors, impacted teeth, fractures in lower or upper jaw, etc. Image processing techniques are applied on these images to detect diseases automatically. Segmentation is an inevitable step in automation to extract disease features. Majority existing literature use semi-automatic method for segmentation of panoramic x-ray. The algorithm proposed in this paper is fully automatic method of segmentation. Findings: Panoramic x-rays give entire view of mouth and facilitate assessment of hard tissue structures of the facial area rather than assessment of dental carries. Segmentation of panoramic x-rays is an inevitable step in automating diagnosis of oral disorders like, tumor, cysts, fracture, etc. In this paper, an algorithm is developed for automatic segmentation of lower jaw and then mandibular bone in dental digital panoramic x-ray. Dental digital panoramic x-ray is a good quality image which does not require noise removal. The segmentation algorithm uses novel strips method where input image is subdivided in number of strips. These strips are further processed to separate lower jaw and mandible from input image. The algorithm is fully automatic and does not involve human intervention at any level. Paper presents analysis of number of strips as 3, 5, 7 and 9. The algorithm presented in this paper gives 93% success for segmentation of lower jaw and 90% success in segmentation of mandible structure when strip count is 5. Applications/Improvement: Strip method focuses ROI and ignores components like teeth, spinal cord shadow, etc. Central strip is useful to segment lower jaw whereas side strips are useful to detect mandible edge points.