Iterative Noise Reduction Algorithm-Based Cone Beam Computed Tomography Image Analysis for Dental Pulp Disease in Root Canal Therapies

This study was aimed to explore the application value of cone beam computed tomography (CBCT) imaging technology based on iterative noise reduction (INR) algorithm in the evaluation of the efficacy of root canal therapy (RCT) for dental pulp disease. Eighty eight dental pulp patients who underwent RCT were taken as the research subjects, and INR algorithm-based CBCT and digital periapical film (DPF) were adopted for examination. Basic information of patients, image performance, and filling quality was recorded. It was found that the INR algorithm-based CBCT images achieved favorable noise reduction effects both within and between slices. Filling length of root canal was evaluated by CBCT and DPF, and differences between them were considerable (P < 0.05). Root canal closeness was evaluated by CBCT and DPF, and substantial differences between them were shown (P < 0.05). Moreover, differences on root canal filling quality examined by CBCT and DPF were also remarkable (P < 0.05). Applying CBCT imaging technology based on INR algorithm to the analysis of the curative effect of dental pulp patients can better retain the image information and can also more accurately evaluate the curative effect of different RCTs.