Perinatal, preterm and paediatric image analysis (2025)最新文献

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Contrast-Invariant Self-supervised Segmentation for Quantitative Placental MRI. 定量胎盘MRI对比不变自监督分割。
Perinatal, preterm and paediatric image analysis (2025) Pub Date : 2026-01-01 Epub Date: 2025-09-23 DOI: 10.1007/978-3-032-05997-0_13
Xinliu Zhong, Ruiying Liu, Emily S Nichols, Xuzhe Zhang, Andrew F Laine, Emma G Duerden, Yun Wang
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引用次数: 0
Consistency Regularization Improves Placenta Segmentation in Fetal EPI MRI Time Series. 一致性正则化改进胎儿EPI MRI时间序列中的胎盘分割。
Perinatal, preterm and paediatric image analysis (2025) Pub Date : 2025-01-01 Epub Date: 2023-10-12 DOI: 10.1007/978-3-031-45544-5_7
Yingcheng Liu, Neerav Karani, Neel Dey, S Mazdak Abulnaga, Junshen Xu, P Ellen Grant, Esra Abaci Turk, Polina Golland
{"title":"Consistency Regularization Improves Placenta Segmentation in Fetal EPI MRI Time Series.","authors":"Yingcheng Liu, Neerav Karani, Neel Dey, S Mazdak Abulnaga, Junshen Xu, P Ellen Grant, Esra Abaci Turk, Polina Golland","doi":"10.1007/978-3-031-45544-5_7","DOIUrl":"10.1007/978-3-031-45544-5_7","url":null,"abstract":"<p><p>The placenta plays a crucial role in fetal development. Automated 3D placenta segmentation from fetal EPI MRI holds promise for advancing prenatal care. This paper proposes an effective semi-supervised learning method for improving placenta segmentation in fetal EPI MRI time series. We employ consistency regularization loss that promotes consistency under spatial transformation of the same image and temporal consistency across nearby images in a time series. The experimental results show that the method improves the overall segmentation accuracy and provides better performance for outliers and hard samples. The evaluation also indicates that our method improves the temporal coherency of the prediction, which could lead to more accurate computation of temporal placental biomarkers. This work contributes to the study of the placenta and prenatal clinical decision-making. Code is available at https://github.com/firstmover/cr-seg.</p>","PeriodicalId":521087,"journal":{"name":"Perinatal, preterm and paediatric image analysis (2025)","volume":"14246 ","pages":"77-87"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13055010/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147641250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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