Department of Urology, Affiliated Xiaoshan Hospital, Hangzhou Normal University, Hangzhou, 311200 Zhejiang, China.
Department of Operating Room, Affiliated Xiaoshan Hospital, Hangzhou Normal University, Hangzhou, 311200 Zhejiang, China.
Comput Math Methods Med. 2022 Apr 19;2022:8002055. doi: 10.1155/2022/8002055. eCollection 2022.
In order to explore the application value of image enhancement algorithm in evaluating pelvic floor rehabilitation training in the prevention of postpartum female pelvic floor dysfunction (FPFD), 70 patients with FPFD were selected as the study subjects and randomly divided into two groups. One group received routine nursing (control group, = 35), and the other group received pelvic floor rehabilitation training based on routine nursing (experimental group, = 35). In ultrasound images based on an image enhancement algorithm, the International Consultation on Incontinence Questionnaire-Short Form (ICIQ-SF), and Pelvic Floor Distress Inventory-20 (PFDI-20) were used to evaluate the efficacy. The results showed that after image enhancement algorithm processing, the image signal-to-noise ratio (SNR), peak signal-to-noise ratio (PSNR), and structural similarity index (SSIM) of ultrasound images of patients with FPFD were significantly improved ( < 0.05); the mean square error (MSE) was significantly decreased ( < 0.05); the diagnostic accuracy of FPFD in the original ultrasound images was 73.34%, and that after image enhancement algorithm processing was significantly improved to be 89.86% ( < 0.05). In addition, the overall clinical response rate of FPFD in the experimental group (82.86%) was obviously higher than that in the control group (51.43%) ( < 0.05). After rehabilitation training, the ICIQ-SF and PFDI-20 scores of patients with FPFD in the two groups suggested a significant decrease ( < 0.05). In summary, using an image enhancement algorithm has a good application prospect in evaluating pelvic floor rehabilitation training in preventing postpartum FPFD and is worthy of further promotion.
为了探讨图像增强算法在评估盆底康复训练预防产后女性盆底功能障碍（FPFD）中的应用价值，选取 70 例 FPFD 患者作为研究对象，随机分为两组。一组接受常规护理（对照组，n=35），另一组在常规护理基础上接受盆底康复训练（实验组，n=35）。在基于图像增强算法的超声图像、国际尿失禁咨询问卷-简短表（ICIQ-SF）和盆底疾病困扰问卷-20 项（PFDI-20）中评估疗效。结果显示，经过图像增强算法处理后，FPFD 患者的超声图像的信噪比（SNR）、峰值信噪比（PSNR）和结构相似性指数（SSIM）均明显提高（ < 0.05）；均方误差（MSE）明显降低（ < 0.05）；原始超声图像对 FPFD 的诊断准确率为 73.34%，经图像增强算法处理后明显提高至 89.86%（ < 0.05）。此外，实验组 FPFD 的整体临床总有效率（82.86%）明显高于对照组（51.43%）（ < 0.05）。康复训练后，两组 FPFD 患者的 ICIQ-SF 和 PFDI-20 评分均明显下降（ < 0.05）。综上所述，图像增强算法在评估盆底康复训练预防产后 FPFD 中具有良好的应用前景，值得进一步推广。
