Gong Xue-Hao, Lu Jun, Liu Jin, Deng Ying-Yuan, Liu Wei-Zong, Huang Xian, Yang Yong-Heng, Xu Qin, Yu Zhi-Ying
Department of Ultrasound, First Affiliated Hospital of Shenzhen University, Second People's Hospital of Shenzhen, Shenzhen, China.
Department of Ultrasound, Second Clinical College of Jinan University, People's Hospital of Shenzhen, Shenzhen, China.
PLoS One. 2015 Oct 30;10(10):e0141046. doi: 10.1371/journal.pone.0141046. eCollection 2015.
In laparoscopic gynecologic surgery, ultrasound has been typically implemented to diagnose urological and gynecological conditions. We applied laparoscopic ultrasonography (using Esaote 7.5~10MHz laparoscopic transducer) on the retrospective analyses of 42 women subjects during laparoscopic extirpation and excision of gynecological tumors in our hospital from August 2011 to August 2013. The objective of our research is to develop robust segmentation technique for isolation and identification of the uterus from the ultrasound images, so as to assess, locate and guide in removing the lesions during laparoscopic operations. Our method enables segmentation of the uterus by the active contour algorithm. We evaluated 42 in-vivo laparoscopic images acquired from the 42 patients (age 39.1 ± 7.2 years old) and selected images pertaining to 4 cases of congenital uterine malformations and 2 cases of pelvic adhesions masses. These cases (n = 6) were used for our uterus segmentation experiments. Based on them, the active contour method was compared with the manual segmentation method by a medical expert using linear regression and the Bland-Altman analysis (used to measure the correlation and the agreement). Then, the Dice and Jaccard indices are computed for measuring the similarity of uterus segmented between computational and manual methods. Good correlation was achieved whereby 84%-92% results fall within the 95% confidence interval in the Student t-test) and we demonstrate that the proposed segmentation method of uterus using laparoscopic images is effective.
在腹腔镜妇科手术中,超声通常用于诊断泌尿系统和妇科疾病。我们应用腹腔镜超声检查(使用百胜7.5~10MHz腹腔镜探头)对2011年8月至2013年8月在我院进行腹腔镜妇科肿瘤切除手术的42例女性患者进行回顾性分析。我们研究的目的是开发强大的分割技术,以便从超声图像中分离和识别子宫,从而在腹腔镜手术中评估、定位并指导切除病变。我们的方法通过主动轮廓算法实现子宫分割。我们评估了从42例患者(年龄39.1±7.2岁)获取的42幅体内腹腔镜图像,并选择了与4例先天性子宫畸形和2例盆腔粘连肿块相关的图像。这6例用于我们的子宫分割实验。在此基础上,由医学专家使用线性回归和布兰德-奥特曼分析(用于测量相关性和一致性)将主动轮廓法与手动分割法进行比较。然后,计算迪赛系数和杰卡德指数以测量计算方法和手动方法分割子宫的相似性。实现了良好的相关性(在学生t检验中,84%-92%的结果落在95%置信区间内),并且我们证明了所提出的使用腹腔镜图像分割子宫的方法是有效的。