胎儿神经超声检查中人工智能的进展：综述
Advancements in Artificial Intelligence for Fetal Neurosonography: A Comprehensive Review.
作者信息
Weichert Jan, Scharf Jann Lennard
机构信息
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.
出版信息
J Clin Med. 2024 Sep 22;13(18):5626. doi: 10.3390/jcm13185626.
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.
对胎儿神经解剖结构进行详细的超声评估在产前诊断中起着至关重要的作用，它能为及时、协调良好的胎儿大脑发育提供有价值的见解，并能检测出甚至可能影响神经发育结果的细微异常。随着人工智能（AI）尤其是医学成像领域的最新进展，利用AI技术提高胎儿神经超声检查的准确性、效率和临床实用性的兴趣与日俱增。这篇重点综述的首要目标是讨论该领域AI应用的最新进展，重点关注图像分析、测量自动化、神经发育结果预测模型、可视化技术及其在临床常规中的整合。
Zotero 插件