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 …

Biometric measurements in fetal ultrasound images are one of the most highly demanding
medical image analysis tasks that can directly contribute to diagnosing fetal diseases …

In recent years, deep learning algorithms have become the standard approach for analyzing
fetal images obtained through ultrasound technology. This chapter surveys the most up-to …

Automating prenatal ultrasound analysis is challenging due to the need for accurate
detection of standard planes and biometric measurements. Existing methods typically rely …

Ultrasound imaging is the most commonly used imaging during pregnancy for tracking the
fetus's growth and monitoring other biological parameters. The assessment of the …

Fetal abdominal subcutaneous soft tissue thickness (FASSTT) is a key indicator in
evaluating fetal growth, development, and nutritional status. Currently, manual measurement …

Because of its compactness, lower cost, and noninvasive nature, ultrasound [1] imaging is a
frequently utilized imaging modality for diagnosing, screening, and treating various …

There are various biometric parameters of the fetus that need to be evaluated to monitor
prenatal diagnosis during pregnancy. Biometric parameters such as head circumference …

Fetal Ultrasound (US) imaging is necessary to prenatal treatment, as it provides information
on the health and development of the fetus. Accurate segmenting is essential but poses …

Medical imaging is important to healthcare because it can be used for early illness
diagnosis, staging, and management, as well as for choosing the most appropriate treatment …