Th(i)s study aimed to realize the automatic diagnosis of fatty degeneration of uterine fibroids. In this study, the traditional nonlocal means (NLM) algorithm was improved by changing the Euclidean distance and introducing a cosine function and applied to the ultrasonic imaging intelligent diagnosis of patients with fatty degeneration of uterine fibroids. Then, the noise reduction effect of the improved NLM algorithm was evaluated based on several indicators, such as peak signal-to-noise ratio (PSNR), mean square error (MSE), contrast-to-noise ratio (CNR), figure of merit (FOM), and structural similarity (SSIM). The accuracy, sensitivity, specificity, and F1 score were adopted to evaluate the improved NLM algorithm for diagnosing fatty degeneration of uterine fibroids, and the Perona-Malik (PM) algorithm and NLM algorithm were used for comparative analysis. The results showed that after the ultrasound images of patients with uterine fibroids were denoised using the improved NLM algorithm, the PSNR, MSE, CNR, FOM, and SSIM were obviously better than the same indicators of the image processed with the PM algorithm and the NLM algorithm, and the differences were statistically significant (P < 0.05). The diagnosis results of patients with fatty degeneration of uterine fibroids found that there was only one patient with missed diagnosis after the ultrasound image was processed with NLM algorithm, and there was no statistical difference between the improved NLM algorithm and the assisted diagnosis accuracy of the pathological examination results (P > 0.05). The average noise reduction time of the PM algorithm, NLM algorithm, and the improved NLM algorithm was 16.38 +/- 4.33 s, 18.01 +/- 5.14 s, and 23.81 +/- 4.62 s, respectively. The diagnosis rate before improvement was 75.0%, the diagnosis accuracy rate for PM was 79.69%, and that after improvement was 85.94%. In summary, the improved NLM algorithm showed a good noise reduction effect on ultrasound images of patients with uterine fibroids, could improve the diagnosis accuracy of fatty degeneration of uterine fibroids, and could assist clinicians in the ultrasound imaging diagnosis of patients with uterine fibroids.
