This brief review summarizes the major applications of artificial intelligence (AI), in particular
deep learning approaches, in molecular imaging and radiation therapy research. To this …

The increasing digitization of medical imaging enables machine learning based
improvements in detecting, visualizing and segmenting lesions, easing the workload for …

Image-to-image translation (I2I) aims to transfer images from a source domain to a target
domain while preserving the content representations. I2I has drawn increasing attention and …

Recent work in machine learning shows that deep neural networks can be used to solve a
wide variety of inverse problems arising in computational imaging. We explore the central …

It is of great significance to apply deep learning for the early diagnosis of Alzheimer's
disease (AD). In this work, a novel tensorizing GAN with high-order pooling is proposed to …

Deep Learning for Medical Image Analysis, Second Edition is a great learning resource for
academic and industry researchers and graduate students taking courses on machine …

Medical image synthesis represents a critical area of research in clinical decision-making,
aiming to overcome the challenges associated with acquiring multiple image modalities for …

Deformable image registration between Computed Tomography (CT) images and Magnetic
Resonance (MR) imaging is essential for many image-guided therapies. In this paper, we …

In recent years, generative adversarial networks (GANs) have gained tremendous popularity
for potential applications in medical imaging, such as medical image synthesis, restoration …

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