In the last decade, Deep Learning (DL) has revolutionized the use of artificial intelligence,
and it has been deployed in different fields of healthcare applications such as image …

Since the advent of U-Net, fully convolutional deep neural networks and its many variants
have completely changed the modern landscape of deep-learning based medical image …

Automated and accurate 3D medical image segmentation plays an essential role in
assisting medical professionals to evaluate disease progresses and make fast therapeutic …

Nowadays, pancreas segmentation in CT scans has gained more and more attention for
computer-assisted diagnosis of inflammation (pancreatitis) or cancer. Despite the thrilling …

Motor imagery (MI) electroencephalography (EEG) classification is an important part of the
brain-computer interface (BCI), allowing people with mobility problems to communicate with …

Pancreatic cancer is the most difficult-to-detect cancer with the highest fatality rate. Pancreas
analysis through abdominal computed tomography (CT) is challenging because the …

Background and objective The size, shape, and position of the pancreas are affected by the
patient characteristics such as age, sex, adiposity. Owing to more complex anatomical …

Purpose Pancreas segmentation is a difficult task because of the high intrapatient variability
in the shape, size, and location of the organ, as well as the low contrast and small footprint of …

Pancreas segmentation is a challenging task in medical image analysis especially for the
patients with pancreatic cancer. First, the images often have poor contrast and blurred …

Background and objective Segmentation of rectal cancerous regions using 2D Magnetic
Resonance Imaging (MRI) images is a critical step in radiation therapy. The shape of rectal …