Automatic identification and segmentation of slice of minimal hiatal dimensions in transperineal ultrasound volumes.
Automatic identification and segmentation of slice of minimal hiatal dimensions in transperineal ultrasound volumes.
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DOI：
10.1002/uog.24810
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发表时间：
2022-10
影响因子：
7.1
通讯作者：
Grob, A. T. M.
中科院分区：
文献类型：
--
作者：
van den Noort, F.;Manzini, C.;van der Vaart, C. H.;van Limbeek, M. A. J.;Slump, C. H.;Grob, A. T. M.
关键词：
开发并验证用于自动选择最小裂孔尺寸（SMHD）切片和经会阴超声（TPUS）容积中泌尿生殖裂孔（UH）分割的工具。手动选择SMHD和分割的UH进行TPUS卷的116名妇女有症状的盆腔器官脱垂（POP）。这些数据用于训练两种深度学习算法。第一种算法被训练以提供SMHD的位置的估计。基于此估计，选择切片并将其馈送到第二算法中，该算法执行UH的自动分割。根据该分割，自动计算UH面积（UHA）、前后径（APD）和冠状径（CD）。在30个TPUS体积的测试集上评估手动和自动选择的SMHD之间的平均绝对距离、手动和自动UH分割之间的重叠（骰子相似性指数（DSI））以及手动和自动UH测量之间的组内相关系数（ICC）。手动和自动选择SMHD之间的平均绝对距离为0.20 cm。手动和自动UH分割之间的所有DSI值均高于0.85。UHA手动和自动UH测量之间的ICC值为0.94（95% CI，0.87-0.97），APD为0.92（95% CI，0.78-0.97），CD为0.82（95% CI，0.66-0.91），证明了极好的一致性。我们的深度学习算法可以在有症状的POP女性的TPUS体积中可靠地自动选择SMHD和UH分割。这些算法可以在TPUS机器的软件中实现，从而减少临床分析时间并简化用于研究和临床目的的TPUS数据检查。版权所有© 2021作者。由John Wiley & Sons Ltd代表国际妇产科超声学会出版的《妇产科超声》。链接文章：有一个评论这篇文章由陈等人。点击这里查看信件。
To develop and validate a tool for automatic selection of the slice of minimal hiatal dimensions (SMHD) and segmentation of the urogenital hiatus (UH) in transperineal ultrasound (TPUS) volumes. Manual selection of the SMHD and segmentation of the UH was performed in TPUS volumes of 116 women with symptomatic pelvic organ prolapse (POP). These data were used to train two deep‐learning algorithms. The first algorithm was trained to provide an estimation of the position of the SMHD. Based on this estimation, a slice was selected and fed into the second algorithm, which performed automatic segmentation of the UH. From this segmentation, measurements of the UH area (UHA), anteroposterior diameter (APD) and coronal diameter (CD) were computed automatically. The mean absolute distance between manually and automatically selected SMHD, the overlap (dice similarity index (DSI)) between manual and automatic UH segmentation and the intraclass correlation coefficient (ICC) between manual and automatic UH measurements were assessed on a test set of 30 TPUS volumes. The mean absolute distance between manually and automatically selected SMHD was 0.20 cm. All DSI values between manual and automatic UH segmentations were above 0.85. The ICC values between manual and automatic UH measurements were 0.94 (95% CI, 0.87–0.97) for UHA, 0.92 (95% CI, 0.78–0.97) for APD and 0.82 (95% CI, 0.66–0.91) for CD, demonstrating excellent agreement. Our deep‐learning algorithms allowed reliable automatic selection of the SMHD and UH segmentation in TPUS volumes of women with symptomatic POP. These algorithms can be implemented in the software of TPUS machines, thus reducing clinical analysis time and simplifying the examination of TPUS data for research and clinical purposes. © 2021 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology. Linked article: There is a comment on this article by Chen et al. Click here to view the Correspondence.
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影响因子：
7.1
作者：
van den Noort, F.;van der Vaart, C. H.;van Stralen, M.
通讯作者：
van Stralen, M.
影响因子：
1.8
作者：
Manzini C;van den Noort F;Grob ATM;Withagen MIJ;van der Vaart CH
通讯作者：
van der Vaart CH
影响因子：
7.7
作者：
Belharbi, Soufiane;Chatelain, Clement;Modzelewski, Romain
通讯作者：
Modzelewski, Romain
影响因子：
7.1
作者：
Sindhwani, N.;Barbosa, D.;Deprest, J.
通讯作者：
Deprest, J.
影响因子：
0.6
作者：
Ritter, Felix;Boskamp, Tobias;Peitgen, Heinz-Otto
通讯作者：
Peitgen, Heinz-Otto