A Novel Approach for Inferior Alveolar Nerve (IAN) Injury Identification Using Panoramic Radiographic Image
T. Karthikeyan and P. Manikandaprabhu*PG and Research Department of Computer Science, PSG College of Arts and Science, Coimbatore, India
Abstract: The technology of medical image processing has extensively involved concentration of relevant experts. Here, panoramic radiographic image is used for analysis. The proposed method consists of five stages namely preprocessing, segmentation, feature extraction, feature selection and classification. In the first stage, anisotropic filter is applied for extracting the noise for experimental image. In the second stage, canny based edge segmentation to segment the image. Then, Statistical texture features are extracted and PCA is the feature selection for the purpose of classification. Finally, the decision tree classifier is used to classify the type of IAN identification image. Thus, the proposed system has been evaluated on a dataset of 50 patients. The proposed system was found efficient in the classification with a success of more than 94% of accuracy. During the dental surgical or implantations, to identify IAN in damage or injury or damage is the main objective of this work.
Keywords: Classification; Decision Tree; Feature Extraction; Image Segmentation; Inferior Alveolar Canal; Inferior Alveolar Nerve; Panoramic Radiography Back to TOC