Department of Gynaecology and Obstetrics, The Fourth Hospital of Changsha, Changsha 410006, Hunan, China.
Department of B-ultrasound Imaging, The Fourth Hospital of Changsha, Changsha 410006, Hunan, China.
Comput Intell Neurosci. 2022 May 27;2022:6951692. doi: 10.1155/2022/6951692. eCollection 2022.
In order to explore the diagnostic value of the improved clustering algorithm of vaginal ultrasound combined with hysteroscopy in abnormal uterine bleeding (AUB), 128 patients diagnosed with AUB in the hospital were selected as the research objects. A -means improved clustering color image segmentation algorithm was designed and applied to AUB vaginal ultrasound image processing. The running time, mean square error (MSE), and peak to signal noise ratio (PSNR) were calculated to evaluate the algorithm, and the sensitivity, specificity, negative likelihood ratio, and positive likelihood ratio were used to evaluate the diagnostic accuracy of the detection method. In addition, combined with hysteroscopy, a comprehensive evaluation of the diagnostic value of abnormal uterine bleeding diseases was implemented. The results showed that compared with the traditional -means clustering algorithm, the running time of the improved -means clustering color image segmentation algorithm in the training set was significantly shortened, the MSE was significantly decreased, and the PSNR was significantly increased ( < 0.05). The sensitivity, specificity, negative likelihood ratio, and positive likelihood ratio (90.5%, 93.2%, 84.3, and 96.3%) of AUB diagnosis were significantly improved in the algorithm of vaginal ultrasound combined with hysteroscopy ( < 0.05). In summary, the combination of vaginal ultrasound and hysteroscopy based on -means improved clustering color image segmentation algorithm can significantly improve the clinical diagnostic accuracy of AUB patients.
为了探讨改进的阴道超声聚类算法联合宫腔镜检查在异常子宫出血（AUB）中的诊断价值，选取我院收治的 128 例 AUB 患者作为研究对象。设计并应用 A-均值改进聚类彩色图像分割算法对 AUB 阴道超声图像进行处理，计算算法的运行时间、均方误差（MSE）和峰值信噪比（PSNR），并用其检测方法的灵敏度、特异度、阴性似然比和阳性似然比来评价诊断准确率。此外，结合宫腔镜检查，对异常子宫出血疾病的诊断价值进行综合评价。结果表明，与传统的 -均值聚类算法相比，改进的 -均值聚类彩色图像分割算法在训练集中的运行时间明显缩短，MSE 明显降低，PSNR 明显升高（<0.05）。阴道超声联合宫腔镜检查的算法可显著提高 AUB 诊断的灵敏度、特异度、阴性似然比、阳性似然比（90.5%、93.2%、84.3%、96.3%）（<0.05）。综上所述，基于 A-均值改进聚类彩色图像分割算法的阴道超声联合宫腔镜检查，可显著提高 AUB 患者的临床诊断准确率。
