An Automated Segmentation Approach using Clustering Technique for Dental Problems Impacted 3rd Molar

Segmentation refers to a subclass of enhancement methods by which a particular object, organ, or image characteristic is extracted from the image data for purposes of visualization and measurement. Segmentation is a central problem of image analysis because it is a prerequisite for most analysis methods, including image registration, shape analysis, motion detection, volume, and area estimation. Unfortunately, there is no common method or class of methods applicable to medical images based on the assumption that the objects of interest have intensity or edge characteristics that allow them to be separated from the background and noise, as well as from each other. In dentistry the wisdom tooth (3rd molar), has the lack of room to erupt, it commonly affects other teeth as they develop and become partially erupted or impacted. To diagnose the problems associated with the wisdom teeth automatically and prepare the radiograph for final analysis, a segmentation algorithm is implemented and followed by post processing stage. The proposed segmentation method aims to extract wisdom teeth using clustering techniques. This information is used further to classify wisdom teeth as impacted, partially erupted, or completely erupted based on distance from IAN.