Jieyun Bai, Zihao Zhou, Zhanhong Ou, Gregor Koehler, Raphael Stock, Klaus Maier-Hein, Marawan Elbatel, Robert Martí, Xiaomeng Li, Yaoyang Qiu, Panjie Gou, Gongping Chen, Lei Zhao, Jianxun Zhang, Yu Dai, Fangyijie Wang, Guénolé Silvestre, Kathleen Curran, Hongkun Sun, Jing Xu, Pengzhou Cai, Lu Jiang, Libin Lan, Dong Ni, Mei Zhong, Gaowen Chen, Víctor M. Campello, Yaosheng Lu, Karim Lekadir
{"title":"PSFHS 挑战报告:从产内超声图像中分割耻骨联合和胎儿头部","authors":"Jieyun Bai, Zihao Zhou, Zhanhong Ou, Gregor Koehler, Raphael Stock, Klaus Maier-Hein, Marawan Elbatel, Robert Martí, Xiaomeng Li, Yaoyang Qiu, Panjie Gou, Gongping Chen, Lei Zhao, Jianxun Zhang, Yu Dai, Fangyijie Wang, Guénolé Silvestre, Kathleen Curran, Hongkun Sun, Jing Xu, Pengzhou Cai, Lu Jiang, Libin Lan, Dong Ni, Mei Zhong, Gaowen Chen, Víctor M. Campello, Yaosheng Lu, Karim Lekadir","doi":"arxiv-2409.10980","DOIUrl":null,"url":null,"abstract":"Segmentation of the fetal and maternal structures, particularly intrapartum\nultrasound imaging as advocated by the International Society of Ultrasound in\nObstetrics and Gynecology (ISUOG) for monitoring labor progression, is a\ncrucial first step for quantitative diagnosis and clinical decision-making.\nThis requires specialized analysis by obstetrics professionals, in a task that\ni) is highly time- and cost-consuming and ii) often yields inconsistent\nresults. The utility of automatic segmentation algorithms for biometry has been\nproven, though existing results remain suboptimal. To push forward advancements\nin this area, the Grand Challenge on Pubic Symphysis-Fetal Head Segmentation\n(PSFHS) was held alongside the 26th International Conference on Medical Image\nComputing and Computer Assisted Intervention (MICCAI 2023). This challenge\naimed to enhance the development of automatic segmentation algorithms at an\ninternational scale, providing the largest dataset to date with 5,101\nintrapartum ultrasound images collected from two ultrasound machines across\nthree hospitals from two institutions. The scientific community's enthusiastic\nparticipation led to the selection of the top 8 out of 179 entries from 193\nregistrants in the initial phase to proceed to the competition's second stage.\nThese algorithms have elevated the state-of-the-art in automatic PSFHS from\nintrapartum ultrasound images. A thorough analysis of the results pinpointed\nongoing challenges in the field and outlined recommendations for future work.\nThe top solutions and the complete dataset remain publicly available, fostering\nfurther advancements in automatic segmentation and biometry for intrapartum\nultrasound imaging.","PeriodicalId":501289,"journal":{"name":"arXiv - EE - Image and Video Processing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"PSFHS Challenge Report: Pubic Symphysis and Fetal Head Segmentation from Intrapartum Ultrasound Images\",\"authors\":\"Jieyun Bai, Zihao Zhou, Zhanhong Ou, Gregor Koehler, Raphael Stock, Klaus Maier-Hein, Marawan Elbatel, Robert Martí, Xiaomeng Li, Yaoyang Qiu, Panjie Gou, Gongping Chen, Lei Zhao, Jianxun Zhang, Yu Dai, Fangyijie Wang, Guénolé Silvestre, Kathleen Curran, Hongkun Sun, Jing Xu, Pengzhou Cai, Lu Jiang, Libin Lan, Dong Ni, Mei Zhong, Gaowen Chen, Víctor M. Campello, Yaosheng Lu, Karim Lekadir\",\"doi\":\"arxiv-2409.10980\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Segmentation of the fetal and maternal structures, particularly intrapartum\\nultrasound imaging as advocated by the International Society of Ultrasound in\\nObstetrics and Gynecology (ISUOG) for monitoring labor progression, is a\\ncrucial first step for quantitative diagnosis and clinical decision-making.\\nThis requires specialized analysis by obstetrics professionals, in a task that\\ni) is highly time- and cost-consuming and ii) often yields inconsistent\\nresults. The utility of automatic segmentation algorithms for biometry has been\\nproven, though existing results remain suboptimal. To push forward advancements\\nin this area, the Grand Challenge on Pubic Symphysis-Fetal Head Segmentation\\n(PSFHS) was held alongside the 26th International Conference on Medical Image\\nComputing and Computer Assisted Intervention (MICCAI 2023). This challenge\\naimed to enhance the development of automatic segmentation algorithms at an\\ninternational scale, providing the largest dataset to date with 5,101\\nintrapartum ultrasound images collected from two ultrasound machines across\\nthree hospitals from two institutions. The scientific community's enthusiastic\\nparticipation led to the selection of the top 8 out of 179 entries from 193\\nregistrants in the initial phase to proceed to the competition's second stage.\\nThese algorithms have elevated the state-of-the-art in automatic PSFHS from\\nintrapartum ultrasound images. A thorough analysis of the results pinpointed\\nongoing challenges in the field and outlined recommendations for future work.\\nThe top solutions and the complete dataset remain publicly available, fostering\\nfurther advancements in automatic segmentation and biometry for intrapartum\\nultrasound imaging.\",\"PeriodicalId\":501289,\"journal\":{\"name\":\"arXiv - EE - Image and Video Processing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - EE - Image and Video Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2409.10980\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - EE - Image and Video Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.10980","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
PSFHS Challenge Report: Pubic Symphysis and Fetal Head Segmentation from Intrapartum Ultrasound Images
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.