Artificial intelligence (AI) has recently become a very popular buzzword, as a consequence
of disruptive technical advances and impressive experimental results, notably in the field of …

Alzheimer's Disease (AD) is an irreversible neurodegenerative disease that results in a
progressive decline in cognitive abilities. Since AD starts several years before the onset of …

Magnetic resonance imaging (MRI) is a widely used neuroimaging technique that can
provide images of different contrasts (ie, modalities). Fusing this multi-modal data has …

Medical image segmentation is the most complex and important task in the field of medical
image processing and analysis, as it is linked to disease diagnosis accuracy. However, due …

The performance of artificial intelligence (AI) for brain MRI can improve if enough data are
made available. Generative adversarial networks (GANs) showed a lot of potential to …

Privacy concerns around sharing personally identifiable information are a major barrier to
data sharing in medical research. In many cases, researchers have no interest in a particular …

Medical images usually suffer from image degradation in clinical practice, leading to
decreased performance of deep learning-based models. To resolve this problem, most …

Machine learning (ML) and deep learning (DL) have achieved great success in different
tasks. These include computer vision, image segmentation, natural language processing …

Deep learning has seen rapid growth in recent years and achieved state-of-the-art
performance in a wide range of applications. However, training models typically requires …

Multi-modal medical images provide complementary soft-tissue characteristics that aid in the
screening and diagnosis of diseases. However, limited scanning time, image corruption and …