In Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology
Deep learning is considered the leading artificial intelligence tool in general image analysis. Deep learning algorithms excel at image recognition, which makes them a valuable tool in the medical imaging field. Obstetrical ultrasound, especially for fetal imaging, has become the gold standard in the detection and diagnosis of fetal malformations. However, ultrasound relies heavily on the operator's experience and, thus, making it unreliable in unexperienced hands. For this purpose, several studies have proposed the use of deep learning models as a supporting tool for sonographers, as an attempt to overcome the intrinsic problems of ultrasound. The use of deep learning in the fetal imaging field has many clinical applications, such as, identification of normal and abnormal fetal anatomy and measurement of fetal biometry. In this review, we provide a comprehensive explanation of the fundamentals of deep learning and fetal imaging, with a special focus on the clinical applicability. This article is protected by copyright. All rights reserved.
Ramirez Zegarra R, Ghi T
2022-Nov-27
