Convolutional neural networks (CNN) have been extensively utilized for image
segmentation tasks, with the U-Net architecture emerging as a classical model in medical …

A U-Net based contour enhanced attention for medical image segmentation Welcome to Journal
of Graphics share: Superintended by China Association for Science and Technology Sponsored …

Medical image segmentation is one of the most challenging tasks in medical image analysis
and widely developed for many clinical applications. While deep learning-based …

Medical image segmentation based on deep learning technics has been more and more
prevalent in recent years. The primary reasons lead to success of those methods are radical …

Image segmentation has been a well-addressed problem in pattern recognition for the last
few decades. As a sub-problem of image segmentation, the background separation in …

With the rapid development and popularization of medical imaging equipment, imaging
technology has been widely used in clinical practice, and it has become an indispensable …

Variational Level Set (LS) has been a widely used method in medical segmentation.
However, it is limited when dealing with multi-instance objects in the real world. In addition …

Objective. Deep convolutional neural networks (CNNs) have been widely applied in medical
image analysis and achieved satisfactory performances. While most CNN-based methods …

A new region-based active contour model in level set formulation is proposed to segment
medical images with poorly defined boundaries. From literature, it is observed that the …

Featured Application Adding level set method to V-Net model in order to improve the
performance of CT image segmentation. Abstract Region of interest (ROI) segmentation is a …