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 …

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 …

Accurate medical image segmentation is essential for diagnosis and treatment planning of
diseases. Convolutional Neural Networks (CNNs) have achieved state-of-the-art …

A brain tumor is an abnormal enlargement of cells if not properly diagnosed. Early detection
of a brain tumor is critical for clinical practice and survival rates. Brain tumors arise in a …

Health complications during the gestation period have evolved as a global issue. These
complications sometimes result in the mortality of the fetus, which is more prevalent in …

Alzheimer's disease (AD) is one of the most important causes of mortality in elderly people,
and it is often challenging to use traditional manual procedures when diagnosing a disease …

Ultrasound is a standard diagnostic tool used during prenatal care to monitor the growth and
development of the fetus. During routine clinical obstetric examinations, fetal ultrasound …

Accurate segmentation of fetal heart in echocardiography images is essential for detecting
the structural abnormalities such as congenital heart defects (CHDs). Due to the wide …

Breast tumor is the second deadliest disease among women around the world. Earlier tumor
diagnosis is extremely important for improving the survival rate. Recent deep-learning …

Most artificial intelligence (AI) research and innovations have concentrated in high-income
countries, where imaging data, IT infrastructures and clinical expertise are plentiful …