As an emerging biomedical image processing technology, medical image segmentation has
made great contributions to sustainable medical care. Now it has become an important …

Generative adversarial networks have gained a lot of attention in the computer vision
community due to their capability of data generation without explicitly modelling the …

Abstract Purpose Since Generative Adversarial Network (GAN) was introduced into the field
of deep learning in 2014, it has received extensive attention from academia and industry …

Deep learning techniques, especially Convolutional Neural Networks (CNN), dominate the
benchmarks for most computer vision tasks. These state-of-the-art results are typically …

Although deep learning models like CNNs have achieved great success in medical image
analysis, the small size of medical datasets remains a major bottleneck in this area. To …

Deep learning (DL) algorithms have rapidly become a robust tool for analyzing medical
images. They have been used extensively for medical image segmentation as the first and …

Skin cancer is a major public health problem that could benefit from computer-aided
diagnosis to reduce the burden of this common disease. Skin lesion segmentation from …

A generative adversarial network (GAN) is one of the most significant research directions in
the field of artificial intelligence, and its superior data generation capability has garnered …

Due to its increasing incidence, skin cancer, and especially melanoma, is a serious health
disease today. The high mortality rate associated with melanoma makes it necessary to …

Skin cancer is a senior public health issue that could profit from computer-aided diagnosis to
decrease the encumbrance of this widespread disease. Researchers have been more …