Advancements in Artificial Intelligence for Fetal Neurosonography: A Comprehensive Review.

artificial intelligence convolutional neural networks fetal machine learning neurosonography prenatal ultrasound

Journal

Journal of clinical medicine
ISSN: 2077-0383
Titre abrégé: J Clin Med
Pays: Switzerland
ID NLM: 101606588

Informations de publication

Date de publication:
22 Sep 2024
Historique:
received: 30 07 2024
revised: 04 09 2024
accepted: 16 09 2024
medline: 28 9 2024
pubmed: 28 9 2024
entrez: 28 9 2024
Statut: epublish

Résumé

The detailed sonographic assessment of the fetal neuroanatomy plays a crucial role in prenatal diagnosis, providing valuable insights into timely, well-coordinated fetal brain development and detecting even subtle anomalies that may impact neurodevelopmental outcomes. With recent advancements in artificial intelligence (AI) in general and medical imaging in particular, there has been growing interest in leveraging AI techniques to enhance the accuracy, efficiency, and clinical utility of fetal neurosonography. The paramount objective of this focusing review is to discuss the latest developments in AI applications in this field, focusing on image analysis, the automation of measurements, prediction models of neurodevelopmental outcomes, visualization techniques, and their integration into clinical routine.

Identifiants

pubmed: 39337113
pii: jcm13185626
doi: 10.3390/jcm13185626
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Auteurs

Jan Weichert (J)

Division of Prenatal Medicine, Department of Gynecology and Obstetrics, University Hospital of Schleswig-Holstein, Ratzeburger Allee 160, 23538 Luebeck, Germany.
Elbe Center of Prenatal Medicine and Human Genetics, Willy-Brandt-Str. 1, 20457 Hamburg, Germany.

Jann Lennard Scharf (JL)

Division of Prenatal Medicine, Department of Gynecology and Obstetrics, University Hospital of Schleswig-Holstein, Ratzeburger Allee 160, 23538 Luebeck, Germany.

Classifications MeSH