Gradient Orientation Mapping Based Fuzzy C-Means Clustering for Digital Dental X-Ray Images

Abstract

In recent development research, the dental radiographic examination generally essential for the diagnosis of dental disorders. Various approaches are used to identify cancer cells. The proposed novel approach, called the Gradient Orientation Mapping Dependent Fuzzy C-Means (GOMB-FCM) algorithm, is being used to evaluate a dental membership function. Using a house, the metric is structured to determine the form that is unusual in dentistry. The overall accuracy of 95 per cent is achieved through the proposed GOMB-FCM process. The result, precision and consistency values for the proposed segmentation method were found to be 96.7%, 95.6% and 98.4% respectively. The similarity of the proposed solution to True Positive
values in the ROC curve means that performance is higher. The comparative analysis with ResNet-50 focuses on different test and training details of 90 to 10 per cent, 80 to 20 per cent and 70 to 3 per cent, respectively, which demonstrates the robustness of the proposed research work. The preliminary results demonstrate the suggested efficiency of the system
relative to other detection strategies