Generative adversarial networks have gained a lot of attention in the computer vision
community due to their capability of data generation without explicitly modelling the …

We look into Generative Adversarial Network (GAN), its prevalent variants and applications
in a number of sectors. GANs combine two neural networks that compete against one …

Generative adversarial models with convolutional neural network (CNN) backbones have
recently been established as state-of-the-art in numerous medical image synthesis tasks …

Coronavirus (COVID-19) is a viral disease caused by severe acute respiratory syndrome
coronavirus 2 (SARS-CoV-2). The spread of COVID-19 seems to have a detrimental effect …

You are holding in your hands… oh, come on, who holds books like this in their hands
anymore? Anyway, you are reading this, and it means that I have managed to release one of …

Multi-contrast MRI protocols increase the level of morphological information available for
diagnosis. Yet, the number and quality of contrasts are limited in practice by various factors …

Curation of large, diverse MRI datasets via multi-institutional collaborations can help
improve learning of generalizable synthesis models that reliably translate source-onto target …

Deep learning techniques have promoted the rise of artificial intelligence (AI) and performed
well in computer vision. Medical image analysis is an important application of deep learning …

Contrast-enhanced magnetic resonance imaging (CEMRI) is crucial for the diagnosis of
patients with liver tumors, especially for the detection of benign tumors and malignant …

Learning-based translation between MRI contrasts involves supervised deep models trained
using high-quality source-and target-contrast images derived from fully-sampled …