Version 1
: Received: 29 July 2024 / Approved: 30 July 2024 / Online: 31 July 2024 (07:47:09 CEST)
How to cite:
Weichert, J.; Scharf, J. L. Advancements in Artificial Intelligence for Fetal Neurosonography: A Comprehensive Review. Preprints2024, 2024072395. https://doi.org/10.20944/preprints202407.2395.v1
Weichert, J.; Scharf, J. L. Advancements in Artificial Intelligence for Fetal Neurosonography: A Comprehensive Review. Preprints 2024, 2024072395. https://doi.org/10.20944/preprints202407.2395.v1
Weichert, J.; Scharf, J. L. Advancements in Artificial Intelligence for Fetal Neurosonography: A Comprehensive Review. Preprints2024, 2024072395. https://doi.org/10.20944/preprints202407.2395.v1
APA Style
Weichert, J., & Scharf, J. L. (2024). Advancements in Artificial Intelligence for Fetal Neurosonography: A Comprehensive Review. Preprints. https://doi.org/10.20944/preprints202407.2395.v1
Chicago/Turabian Style
Weichert, J. and Jann Lennard Scharf. 2024 "Advancements in Artificial Intelligence for Fetal Neurosonography: A Comprehensive Review" Preprints. https://doi.org/10.20944/preprints202407.2395.v1
Abstract
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 scoping review is to discuss the latest developments in AI applications in this field, focusing on image analysis, automation of measurements, prediction models for neurodevelopmental outcomes, visualization techniques, and integration into clinical routine.
Medicine and Pharmacology, Obstetrics and Gynaecology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
