Segmentation and Feature Extraction of Panoramic Dental X-Ray Images

Abstract

Automating the process of analysis of Panoramic X-Ray images is important to help dentist procedures and diagnosis. Tooth segmentation from the radiographic images and feature extraction are essential steps. The authors propose a segmentation approach based on mathematical morphology, quadtree decomposition for mask generation, thresholding, and snake models. The feature extraction stage is steered by a shape model based on Principal Component Analysis (PCA). First, the authors take the quadtree decomposition of a low-pass version of the original image and select the smallest blocks to generate a mask. Then, the original image is processed by Otsu’s thresholding. The result is improved by morphological operators and the quadtree mask is applied to address overlapping, a common problem in X-ray images. The obtained regions are searched and the larger ones are selected to find tooth candidates. The boundary of the obtained regions are extracted and aligned with the shape model in order to recognize the target tooth (molar). The selected curve is used in a search method to initialize a snake technique. Finally, morphometric data extraction is performed to obtain tooth measurements for dentist diagnosis. Experiments show the advantages of the proposed method to extract teeth from X-Ray images and discuss its drawbacks.

Advancing Dental Diagnostics: A Review of Artificial Intelligence Applications and Challenges in Dentistry

“…As for the papers not previously addressed, namely [30][31][32][33][34][35][36][37][38][39][40], it is evident that a significant limitation present in these studies is the lack of comprehensive details regarding the dataset employed. These articles notably omitted crucial information that would otherwise contribute to a more thorough understanding and evaluation of their respective research methodologies and findings.…”

“…This decade has seen a tremendous development in dental diagnostic tools due to advances in artificial intelligence (AI), machine learning, and automated image analysis. It all started in 2010, when Pedro H. M. Lira and Gilson A. Giraldi published their seminal work on automating the examination of panoramic X-ray images for dental purposes, with an emphasis on feature extraction and teeth segmentation [30]. But difficulties like handling teeth that overlapped and the absence of comprehensive dataset information brought attention to the first obstacles.…”