Cone-Beam Computed Tomography Image Features under Intelligent Three-Dimensional Reconstruction Algorithm in the Evaluation of Intraoperative and Postoperative Curative Effect of Dental Pulp Disease Using Root Canal Therapy

Abstract

Objective. The objective of this study was to analyze the application effect of algorithm-based three-dimensional reconstruction of cone-beam computed tomography (CBCT) images in the treatment of dental pulp disease (DPD) and the evaluation of the curative effect after treatment. Methods. 120 patients with DPD in hospital were selected as the research objects. In this study, based on the regridding model in the algorithm, the mapping relationship between the undersampled CBCT image and the fully sampled CBCT image was connected, and a model that can be used for image restoration and reconstruction was obtained after training. The algorithm model was used to reconstruct and repair the CBCT images of the research objects, and then, the reconstructed CBCT images were segmented based on the improved level set algorithm. After that, it analyzed and compared the accuracy of X-ray and CBCT based on three-dimensional reconstruction for the diagnosis accuracy of DPD and compared the average bone density of patients and the effect of root canal filling in each time period after root canal treatment. Result. After the image was reconstructed with the regridding model, a CBCT image of the patient’s teeth with less noise and clearer structure was obtained. The segmentation accuracy of the level set algorithm reached 85.5% on average, and the undersegmentation rate (UR) and the over-segmentation rate (OR) were both less than 6%. The diagnostic rates of X-ray and three-dimensional CBCT examination of DPD were 43.7% and 100%, respectively, and the difference was statistically significant ( $P<0.05$ ). Under the monitoring of the three-dimensional reconstruction of CBCT technology, the average bone density of the test group patients after 12 months of root canal treatment was the same as that of healthy people. Under X-ray examination, the average bone density of the test group patients was still lower than that of healthy people after 12 months of root canal treatment. Under the three-dimensional reconstruction of CBCT, the underfilling rate of patients after root canal treatment was 5%, the proper filling rate was 85%, and the overfilling rate was 10%. Conclusion. In summary, the CBCT reconstructed by the intelligent three-dimensional algorithm was effectively improved, which enhanced the image quality and segmentation efficiency. Analysis on diagnosis efficiency and treatment effect proved that CBCT can be an effective method to evaluate the initial curative effect of DPD treatment during and after the surgery and can provide valuable information in future dental treatment, thereby enhancing the success rate of DPD using root canal therapy.