Semi‐automatic outlining of levator hiatus

ABSTRACT 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 © 2015 ISUOG. Published by John Wiley & Sons Ltd.