The renaissance of deep learning has provided promising solutions to various tasks. While
conventional deep learning models are constructed for a single specific task, multi-task deep …

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 …

The apical four-chamber (A4C) view in fetal echocardiography is a prenatal examination
widely used for the early diagnosis of congenital heart disease (CHD). Accurate …

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 …

One way of resolving the problem of scarce and expensive data in deep learning for medical
applications is using transfer learning and fine-tuning a network which has been trained on …

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 …

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 …

We explore the potential of CNN-based models for gallbladder cancer (GBC) detection from
ultrasound (USG) images as no prior study is known. USG is the most common diagnostic …