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 …

Image segmentation is vital to medical image analysis and clinical diagnosis. Recently,
convolutional neural networks (CNNs) have achieved tremendous success in this task …

Medical image segmentation is a critical and important step for developing computer-aided
system in clinical situations. It remains a complicated and challenging task due to the large …

Image segmentation is a primary task in many medical applications. Recently, many deep
networks derived from U-Net has been extensively used in various medical image …

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 …

Accurate medical image segmentation plays a crucial role in computer-assisted diagnosis
and monitoring. However, due to the complexity of medical images and the limitations of …

Accurate segmentation of anatomic structure is an essential task for biomedical image
analysis. Recent popular object contours regression based segmentation methods have …

Image segmentation is a fundamental topic in image processing and has been studied for
many decades. Deep learning-based supervised segmentation models have achieved state …

Medical image segmentation is a crucial but challenging task for computer-aided diagnosis.
In recent years, fully convolutional network-based methods have been widely applied to …

In recent years, semantic segmentation in deep learning has been widely applied in medical
image segmentation, leading to the development of numerous models. Convolutional …