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 …

Deep learning has revolutionized image processing and achieved the-state-of-art
performance in many medical image segmentation tasks. Many deep learning-based …

Deep neural networks have brought remarkable breakthroughs in medical image analysis.
However, due to their data-hungry nature, the modest dataset sizes in medical imaging …

Although generative adversarial networks (GANs) can produce large datasets, their limited
diversity and fidelity have been recently addressed by denoising diffusion probabilistic …

Multiple Sclerosis (MS) is a type of brain disease which causes visual, sensory, and motor
problems for people with a detrimental effect on the functioning of the nervous system. In …

Neurological and psychiatric diseases have high degrees of genetic and pathophysiological
heterogeneity, irrespective of clinical manifestations. Traditional medical paradigms have …

Abstract Recently, deep learning (DL)‐based methods for the generation of synthetic
computed tomography (sCT) have received significant research attention as an alternative to …

Recent progress in artificial intelligence and machine learning has led to the growth of
research in every aspect of life including the health care domain. However, privacy risks and …

Purpose In radiotherapy, MRI is used for target volume and organs-at-risk delineation for its
superior soft-tissue contrast as compared to CT imaging. However, MRI does not provide the …

Artificial intelligence (AI) is a branch of computer science that includes research in robotics,
language recognition, image recognition, natural language processing, and expert systems …