Segmentation of the fetal and maternal structures, particularly intrapartum ultrasound imaging as advocated by the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG) for monitoring labor progression, is a crucial first step for quantitative diagnosis and clinical decision-making. This requires specialized analysis by obstetrics professionals, in a task that i) is highly time- and cost-consuming and ii) often yields inconsistent results. The utility of automatic segmentation algorithms for biometry has been proven, though existing results remain suboptimal. To push forward advancements in this area, the Grand Challenge on Pubic Symphysis-Fetal Head Segmentation (PSFHS) was held alongside the 26th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2023). This challenge aimed to enhance the development of automatic segmentation algorithms at an international scale, providing the largest dataset to date with 5,101 intrapartum ultrasound images collected from two ultrasound machines across three hospitals from two institutions. The scientific community's enthusiastic participation led to the selection of the top 8 out of 179 entries from 193 registrants in the initial phase to proceed to the competition's second stage. These algorithms have elevated the state-of-the-art in automatic PSFHS from intrapartum ultrasound images. A thorough analysis of the results pinpointed ongoing challenges in the field and outlined recommendations for future work. The top solutions and the complete dataset remain publicly available, fostering further advancements in automatic segmentation and biometry for intrapartum ultrasound imaging.

中文翻译：

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PSFHS 激发报告：产时超声图像中的耻骨联合和胎头分割


分割胎儿和母体结构，特别是国际妇产科超声学会 （ISUOG） 倡导的用于监测分娩进展的产时超声成像，是定量诊断和临床决策的关键第一步。这需要产科专业人员进行专业分析，这项任务 i） 非常耗时和成本，并且 ii） 经常产生不一致的结果。自动分割算法在生物统计学中的效用已经得到证明，尽管现有结果仍然不理想。为了推动这一领域的进步，耻骨联合-胎儿头部分割 （PSFHS） 大挑战与第 26 届医学图像计算和计算机辅助干预国际会议 （MICCAI 2023） 一起举行。这项挑战赛旨在加强国际范围内自动分割算法的开发，提供迄今为止最大的数据集，其中包含从两个机构的三家医院的两台超声机收集的 5,101 张产时超声图像。科学界的热情参与导致在初始阶段从 193 名注册者的 179 个参赛作品中选出前 8 名，进入比赛的第二阶段。这些算法提升了产时超声图像自动 PSFHS 的最新技术水平。对结果的全面分析指出了该领域持续存在的挑战，并概述了对未来工作的建议。顶级解决方案和完整数据集仍然公开可用，促进了产时超声成像的自动分割和生物测量的进一步进步。