Department of Gynaecology, The First People's Hospital of Huaihua, Huaihua, 418000 Hunan, China.
Comput Math Methods Med. 2022 May 25;2022:2645607. doi: 10.1155/2022/2645607. eCollection 2022.
The aim of this study was to explore the application value of transvaginal color Doppler ultrasound based on the improved mean shift algorithm in the diagnosis of idiopathic premature ovarian failure (POF). In this study, 80 patients with idiopathic POF were selected and included in the experimental group, and 40 volunteers who underwent health examinations during the same period were selected and included in the control group, who underwent transvaginal Doppler ultrasound examination. At the same time, an improved mean shift algorithm was proposed based on artificial intelligence technology and applied to ultrasound image processing. In addition, the ovarian artery parameters of patients were compared in two groups, including peak systolic flow rate (PSV), diastolic flow rate (EDV), resistance index (RI), and pulsatile index (PI). The results showed that the relative difference degree (RDD) of the segmentation results of the algorithm in this study was significantly lower than that of Snake, Live_wire, and the traditional mean shift algorithm, while the relative overlap degree (ROD) and Dice coefficient were opposite, and the differences were significant (<0.05). The mediolateral diameter of control group was 2.87±0.31cm, and the anteroposterior diameter was 1.86±0.28 cm; while those were 2.11±0.36 cm and 1.13±0.34 cm, respectively, in the experimental group, showing significant differences between the groups (<0.05). Of the 80 patients in the experimental group, 132 cases with ovarian arteries were found; among 40 patients in the experimental group, 76 cases were found with ovarian arteries, and the hemodynamic detection rate of the experimental group was significantly lower than that of the control group (<0.05). The ovarian artery parameters PI, RI, and S/D of the experimental group were significantly higher than those of the control group, and the differences were statistically significant (<0.05). The results showed that the segmentation results of the improved algorithm in this study were more superior to the segmentation results of other algorithms. The regional information loss of the segmentation results was not serious, and the resolution was higher and the definition was higher. The transvaginal color Doppler ultrasound based on the artificial intelligence segmentation algorithm can clearly show the functional status and hemodynamics of the patient's ovaries. The ovarian artery parameters PI and RI can be used as specific indicators for evaluating the POF.
本研究旨在探讨基于改进均值漂移算法的经阴道彩色多普勒超声在特发性卵巢早衰（POF）诊断中的应用价值。本研究选取 80 例特发性 POF 患者为实验组，同期选取 40 例健康体检志愿者为对照组，均行经阴道多普勒超声检查。同时，基于人工智能技术提出了一种改进的均值漂移算法，并将其应用于超声图像处理。此外，比较两组患者的卵巢动脉参数，包括收缩期峰值流速（PSV）、舒张末期流速（EDV）、阻力指数（RI）和搏动指数（PI）。结果显示，本研究算法的分割结果相对差异度（RDD）明显低于 Snake、Live_wire 和传统均值漂移算法，而相对重叠度（ROD）和 Dice 系数则相反，差异具有统计学意义（<0.05）。对照组的横径为 2.87±0.31cm，前后径为 1.86±0.28cm；实验组分别为 2.11±0.36cm 和 1.13±0.34cm，组间差异有统计学意义（<0.05）。实验组 80 例患者中，共发现卵巢动脉 132 例；实验组 40 例患者中，共发现卵巢动脉 76 例，实验组的血流动力学检出率明显低于对照组（<0.05）。实验组的卵巢动脉参数 PI、RI 和 S/D 明显高于对照组，差异有统计学意义（<0.05）。结果表明，本研究改进算法的分割结果明显优于其他算法的分割结果。分割结果的区域信息损失不严重，分辨率更高，定义更高。基于人工智能分割算法的经阴道彩色多普勒超声能清晰显示患者卵巢的功能状态和血流动力学。卵巢动脉参数 PI 和 RI 可作为评估 POF 的特异性指标。
