ArticleMagnetic resonance in medicine2026
Scanner-based real-time automated volumetry reporting of the fetus, amniotic fluid, placenta, and umbilical cord for fetal MRI at 0.55T.
Article in Magnetic resonance in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Automated fetal magnetic resonance imaging lung segmentation for rapid lung volume estimation across diverse pulmonary hypoplasia phenotypes.Pediatric radiology · 2026Article
- Normative volumetric growth modeling of the whole fetal body, placenta, and amniotic fluid for three-dimensional T2-weighted magnetic resonance imaging.Pediatric radiology · 2026Article
- Scanner-based real-time automated volumetry reporting of the fetus, amniotic fluid, placenta, and umbilical cord for fetal MRI at 0.55T.Magnetic resonance in medicine · 2026Article
- Normative volumetric growth modeling of the whole fetal body, placenta and amniotic fluid for 3-dimensional T2-weighted magnetic resonance imaging.medRxiv : the preprint server for health sciences · 2026Article
- Predicting adverse perinatal outcomes in small-for-gestational-age fetuses using MRI, ultrasound, and clinical data.Radiology advances · 2025Article
Corrections and comments
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Authors and funding
21 authors.
Funding
Abstract
purposeThis work aims to enable real-time automated intra-uterine volumetric reporting and fetal weight estimation for fetal MRI, deployed directly on the scanner.
methodsA multi-region segmentation nnUNet was trained on 146 images of 73 fetal subjects (coronal and axial orientations) for the parcellation of the fetal head, fetal body, placenta, amniotic fluid, and umbilical cord from whole uterus bSSFP stacks. A reporting tool was then developed to integrate the segmentation outputs into an automated report, providing volumetric measurements, fetal weight estimations, and z-score visualizations. The complete pipeline was subsequently deployed on a 0.55T MRI scanner, enabling real-time inference and fully automated reporting in the duration of the acquisition.
resultsThe segmentation pipeline was quantitatively and retrospectively evaluated on 36 stacks of 18 fetal subjects and demonstrated sufficient performance for all labels, with high scores (
conclusionsThis work demonstrated the feasibility of multi-regional intra-uterine segmentation, fetal weight estimation, and automated reporting in real-time. This study provides a robust baseline solution for the integration of fully automated scanner-based measurements into fetal MRI reports.
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