The advent of artificial intelligence-generated content (AIGC) represents a pivotal moment in
the evolution of information technology. With AIGC, it can be effortless to generate high …

Despite technological and medical advances, the detection, interpretation, and treatment of
cancer based on imaging data continue to pose significant challenges. These include inter …

Abstract We introduce Infinigen Indoors a Blender-based procedural generator of
photorealistic indoor scenes. It builds upon the existing Infinigen system which focuses on …

In recent years, considerable work has been conducted on the development of synthetic
medical images, but there are no satisfactory methods for evaluating their medical suitability …

In many clinical and research settings, the scarcity of high-quality medical imaging datasets
has hampered the potential of artificial intelligence (AI) clinical applications. This issue is …

Large annotated datasets are required for training deep learning models, but in medical
imaging data sharing is often complicated due to ethics, anonymization and data protection …

Early detection and assessment of polyps play a crucial role in the prevention and treatment
of colorectal cancer (CRC). Polyp segmentation provides an effective solution to assist …

The lack of large datasets and high-quality annotated data often limits the development of
accurate and robust machine-learning models within the medical and surgical domains. In …

This paper provides an overview of the Medical Visual Question Answering for
Gastrointestinal Tract (MedVQA-GI) challenge held at ImageCLEF 2023, a new challenge …

Deep learning (DL) methods have recently become state-of-the-art in most automated
medical image segmentation tasks. Some of the biggest challenges in this field are related …