The remarkable performance of the Transformer architecture in natural language processing
has recently also triggered broad interest in Computer Vision. Among other merits …

Artificial intelligence and machine learning are driving a paradigm shift in medicine,
promising data-driven, personalized solutions for managing diabetes and the excess …

Foundation models in deep learning are characterized by a single large-scale model trained
on vast amounts of data serving as the foundation for various downstream tasks. Foundation …

The paucity of high-quality medical imaging datasets could be mitigated by machine
learning models that generate compositionally diverse images that faithfully represent …

Since the era of deep learning, convolutional neural networks (CNNs) and vision
transformers (ViTs) have been extensively studied and widely used in medical image …

Digital pathology has transformed the traditional pathology practice of analyzing tissue
under a microscope into a computer vision workflow. Whole-slide imaging allows …

Artificial intelligence (AI) advancements, especially deep learning, have significantly
improved medical image processing and analysis in various tasks such as disease …

Foundation vision-language models are currently transforming computer vision, and are on
the rise in medical imaging fueled by their very promising generalization capabilities …

evolved separately and have never worked together well. Thus, it is not surprising that
radiologists often work with disjointed system integrations and clashing user interfaces …

Foundation models have significantly advanced medical image analysis through the pre-
train fine-tune paradigm. Among various fine-tuning algorithms, Parameter-Efficient Fine …