Deep-learning (DL) algorithms are becoming the standard for processing ultrasound (US)
fetal images. A number of survey papers in the field is today available, but most of them are …

Artificial intelligence (AI) is being increasingly adopted in medical research and applications.
Medical AI devices have continuously been approved by the Food and Drug Administration …

Transperineal ultrasound imaging in the mid-sagittal plane can potentially enable the
objective quantification of the level of fetal head descent in the birth canal by measuring the …

The objective is to summarize the current use of artificial intelligence (AI) in obstetric
ultrasound. PubMed, Cochrane Library, and ClinicalTrials. gov databases were searched …

Due to advancements in ultrasound techniques, the focus of antenatal ultrasound screening
is moving towards the first trimester of pregnancy. The early first trimester however remains …

The segmentation of cardiac chambers and the quantification of clinical functional metrics in
dynamic echocardiography are the keys to the clinical diagnosis of heart disease. Identifying …

Objective. This work investigates the use of deep convolutional neural networks (CNN) to
automatically perform measurements of fetal body parts, including head circumference …

Ultrasound based estimation of fetal biometry is extensively used to diagnose prenatal
abnormalities and to monitor fetal growth, for which accurate segmentation of the fetal …

Artificial intelligence (AI) has gained prominence in medical imaging, particularly in
obstetrics and gynecology (OB/GYN), where ultrasound (US) is the preferred method. It is …

Biometric parameter measurements are powerful tools for evaluating a fetus's gestational
age, growth pattern, and abnormalities in a 2D ultrasound. However, it is still challenging to …