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 …

Deep learning is transforming most areas of science and technology, including electron
microscopy. This review paper offers a practical perspective aimed at developers with …

Background and objective Examination of head shape and brain during the fetal period is
paramount to evaluate head growth, predict neurodevelopment, and to diagnose fetal …

Artificial intelligence (AI) can support clinical decisions and provide quality assurance for
images. Although ultrasonography is commonly used in the field of obstetrics and …

Prenatal ultrasonography is the most crucial imaging modality during pregnancy. However,
problems such as high fetal mobility, excessive maternal abdominal wall thickness, and inter …

Several reviews have been conducted regarding artificial intelligence (AI) techniques to
improve pregnancy outcomes. But they are not focusing on ultrasound images. This survey …

Objective. Deep learning (DL) methods have been widely utilized in ultrasound (US) image
segmentation tasks. However, current DL segmentation methods for US images are typically …

Monitoring fetal growth in utero is crucial to anomaly diagnosis. However, current computer‐
vision models struggle to accurately assess the key metrics (ie, head circumference and …

Purpose To investigate if artificial intelligence can identify fetus intracranial structures in
pregnancy week 11–14; to provide an automated method of standard and non-standard …

Checking up on the health of the fetus during pregnancy is an important issue that should be
taken into account. Ultrasound imaging, as one useful medical imaging technique, helps …