Light-sheet fluorescence microscopy has transformed our ability to visualize and
quantitatively measure biological processes rapidly and over long time periods. In this …

Despite its astounding success in learning deeper multi-dimensional data, the performance
of deep learning declines on new unseen tasks mainly due to its focus on same-distribution …

While deep learning models have become the predominant method for medical image
segmentation, they are typically not capable of generalizing to unseen segmentation tasks …

Compared to traditional machine learning, deep learning can learn deeper abstract data
representation and understand scattered data properties. It has gained considerable …

Skin diseases are one of the most common ailments affecting humans. Artificial intelligence
based on deep learning can significantly improve the efficiency of identifying skin disorders …

Recent developments in deep learning have enabled data-driven algorithms that can reach
human-level performance and beyond. The development and deployment of medical image …

Stroke, particularly ischemic stroke, is a major cause of disability and one of the leading
causes of adult mortality worldwide. Early and prompt management of stroke patients can …

In the field of pathology, the scarcity of certain diseases and the difficulty of annotating
images hinder the development of large, high-quality datasets, which in turn affects the …

Medical image segmentation has seen significant progress through the use of supervised
deep learning. Hereby, large annotated datasets were employed to reliably segment …

Vision Transformer (ViT) is emerging as a new leader in computer vision with its outstanding
performance in many tasks (eg, ImageNet-22k, JFT-300M). However, the success of ViT …