Artificial Intelligence in Fetal MRI: Principles, Applications, Limitations, and Future Directions.

Journal: Clinical obstetrics and gynecology
Published Date:

Abstract

Artificial intelligence (AI) offers solutions to overcome limitations of fetal MRI, including motion, low signal-to-noise ratio, and slice misregistration. This review summarizes current AI applications in fetal MRI, focusing on image enhancement, automated segmentation, quantitative analysis, and emerging multimodal approaches. AI improves reconstruction, denoising, motion correction, and volumetric assessment, and supports tasks such as gestational-age estimation and anomaly detection. However, most studies rely on small, single-center data sets with limited external validation. Robust multicenter data, standardized protocols, and transparent evaluation frameworks are required before AI can be reliably integrated into routine prenatal imaging.

Authors

  • Romain Corroenne
    EA fetus 7328 and LUMIERE Platform, University of Paris.
  • Laurence Bussieres
    EA fetus 7328 and LUMIERE Platform, University of Paris.
  • David Grevent
    EA fetus 7328 and LUMIERE Platform, University of Paris.
  • Laurent J Salomon
    Maternité Necker-Enfants Malades, Assistance publique - Hôpitaux de Paris (AP-HP), Université Paris Descartes, Paris, France.

Keywords

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