Accurate and automatic segmentation of medical images can greatly assist the clinical
diagnosis and analysis. However, it remains a challenging task due to (1) the diversity of …

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 …

In this paper, we propose a novel image segmentation method to tackle two critical problems
of medical image, which are (i) ambiguity of structure boundary in the medical image domain …

The incidence of infertility is continuously increasing nearly all over the world in recent
years, and novel methods for accurate assessment are of great need. Artificial Intelligence …

In this paper, we present T-Net, a fully convolutional net-work particularly well suited for
resource constrained andmobile devices, which cannot cater for the computationalresources …

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 …

In this work, we propose to address the existing problem of biomedical image segmentation
that often produces results, which fail to capture the exact contours of the target and suffer …

Manual assessment of biomedical imaging based diagnostics is limited as it is time-
consuming and subjective. Bio-inspired diagnostics applications on embedded and mobile …

Background Endometrial thickness is an essential factor affecting female fertility. Clinically,
ultrasound imaging is the first choice for the examination of uterine and endometrial-related …

In this review of the most recent applications of deep learning to ultrasound imaging, the
architectures of deep learning networks are briefly explained for the medical imaging …