Ultrasonic Elastography Combined with Human Papilloma Virus Detection Based on Intelligent Denoising Algorithm in Diagnosis of Cervical Intraepithelial Neoplasia

The aim of this research was to study the application of ultrasonic elastography combined with human papilloma virus (HPV) detection based on bilateral filter intelligent denoising algorithm in the diagnosis of cervical intraepithelial neoplasia (CIN) and provide a theoretical basis for clinical diagnosis and treatment of CIN. In this study, 100 patients with cervical lesions were selected as research objects and randomly divided into control group and experimental group, with 50 cases in each group. Patients in control group and experimental group were diagnosed by ultrasonic elastography combined with HPV detection. The experimental group used the optimized image map of bilateral filter intelligent denoising algorithm for denoising and optimization, while the control group did not use optimization, and the differences between them were analyzed and compared. The diagnostic effects of the two groups were compared. As a result, the three accuracy rates of the experimental group were 95%, 95%, and 98%, respectively; the three sensitivity rates were 96%, 92%, and 94%, respectively; and the three specificity rates were 99%, 97%, and 98%, respectively. In the control group, the three accuracy rates were 84%, 86%, and 84%, respectively; the three sensitivity rates were 88%, 84%, and 86%, respectively; and the three specificity rates were 81%, 83%, and 88%, respectively. The accuracy, sensitivity, and specificity of experiment group were significantly higher than those of control group, and the difference was statistically significant (P < 0.05). In summary, the bilateral filter intelligent denoising algorithm has a good denoising effect on the ultrasonic elastography. The ultrasonic image processed by the algorithm combined with HPV detection has a better diagnosis of CIN.