Deep learning has been widely used for medical image segmentation and a large number of
papers has been presented recording the success of deep learning in the field. A …

Deep learning has revolutionized image processing and achieved the-state-of-art
performance in many medical image segmentation tasks. Many deep learning-based …

In the past few years, convolutional neural networks (CNNs) have achieved milestones in
medical image analysis. In particular, deep neural networks based on U-shaped architecture …

Over the past decade, deep convolutional neural networks have been widely adopted for
medical image segmentation and shown to achieve adequate performance. However, due …

Image segmentation is a critical and important step in (GEographic) Object-Based Image
Analysis (GEOBIA or OBIA). The final feature extraction and classification in OBIA is highly …

Medical image segmentation is an important step in medical image analysis. With the rapid
development of a convolutional neural network in image processing, deep learning has …

Recent years have witnessed enormous progress in AI-related fields such as computer
vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it …

Segmentation is a fundamental task in medical image analysis. However, most existing
methods focus on primary region extraction and ignore edge information, which is useful for …

Automatic segmentation is a fundamental task in computer-assisted medical image analysis.
Convolutional neural networks (CNNs) have been widely used for medical image …

In recent years, computer-aided diagnosis has become an increasingly popular topic.
Methods based on convolutional neural networks have achieved good performance in …