Semi-automatic outlining of levator hiatus
Semi-automatic outlining of levator hiatus
复制标题
DOI：
10.1002/uog.15777
复制
发表时间：
2016-07-01
影响因子：
7.1
通讯作者：
Deprest, J.
中科院分区：
文献类型：
--
作者：
Sindhwani, N.;Barbosa, D.;Deprest, J.
目的建立一个半自动化的轮廓工具的提肌裂孔，以减少观察者之间的差异和加快analysis.Methods建议的自动裂孔分割（AHS）算法需要一个C平面图像，在平面上的最小裂孔尺寸，并手动定义垂直裂孔限制作为输入。然后，AHS通过在强度不变的边缘图上拟合预定义的模板来创建初始轮廓，该边缘图使用B样条显式活动表面框架进一步细化。使用91个代表性C平面图像测试AHS。人工获得参考裂孔轮廓，并由三名独立观察员与AHS轮廓进行比较。平均绝对距离（MAD），Hausdorff距离和Dice和Jaccard系数被用来量化分割精度。这些指标中的每一个都计算了计算机观察者差异（COD）和观察者间差异。威廉姆斯指数用于检验零假设，即自动化方法与操作员的一致性至少与操作员之间的一致性一样好。两种方法之间的协议进行了评估，使用组内相关系数（ICC）和Bland-Altman plots.Results的AHS轮廓匹配良好，与手动的（中位数COD，2.10（四分位距（IQR），1.54）毫米的MAD）。所有质量指标的威廉姆斯指数均大于或接近1，表明该算法在评定者间变异性方面的表现至少与手动参考一样好。与手动相比，使用AHS获取轮廓时，使用每个指标的观察者间差异显着降低，并且实现了更高的ICC（0.93）。Bland-Altman图显示两种方法之间的偏倚可忽略不计。使用AHS的平均时间为7.07（IQR，3.49）s，而手动勾勒需要21.31（IQR，5.43）s，因此几乎快了三倍。使用AHS，在一般情况下，裂孔可以完全使用三个点，两个初始化和一个手动adjustment.Conclusions，我们提出了一种方法，用于跟踪提肛裂孔轮廓与最小的用户输入。AHS是快速，强大和可靠的，并提高评分员之间的协议。版权所有（C）2015 ISUOG.出版社：John Wiley & Sons Ltd
Objective To create a semi-automated outlining tool for the levator hiatus, to reduce interobserver variability and and speed up analysis.Methods The proposed automated hiatus segmentation (AHS) algorithm takes a C-plane image, in the plane of minimal hiatal dimensions, and manually defined vertical hiatal limits as input. The AHS then creates an initial outline by fitting predefined templates on an intensity-invariant edge map, which is further refined using the B-spline explicit active surfaces framework. The AHS was tested using 91 representative C-plane images. Reference hiatal outlines were obtained manually and compared with the AHS outlines by three independent observers. The mean absolute distance (MAD), Hausdorff distance and Dice and Jaccard coefficients were used to quantify segmentation accuracy. Each of these metrics was calculated both for computer-observer differences (COD) and for interobserver differences. The Williams index was used to test the null hypothesis that the automated method would agree with the operators at least as well as the operators agreed with each other. Agreement between the two methods was assessed using the intraclass correlation coefficient (ICC) and Bland-Altman plots.Results The AHS contours matched well with the manual ones (median COD, 2.10 (interquartile range (IQR), 1.54) mm for MAD). The Williams index was greater than or close to 1 for all quality metrics, indicating that the algorithm performed at least as well as did the manual references in terms of interrater variability. The interobserver differences using each of the metrics were significantly lower, and a higher ICC was achieved (0.93), when obtaining outlines using the AHS compared with manually. The Bland-Altman plots showed negligible bias between the two methods. Using the AHS took a median time of 7.07 (IQR, 3.49) s, while manual outlining took 21.31 (IQR, 5.43) s, thus being almost three-fold faster. Using the AHS, in general, the hiatus could be outlined completely using only three points, two for initialization and one for manual adjustment.Conclusions We present a method for tracing the levator hiatal outline with minimal user input. The AHS is fast, robust and reliable and improves interrater agreement. Copyright (C) 2015 ISUOG. Published by John Wiley & Sons Ltd.