Object With the development of deep learning, the number of training samples for medical
image-based diagnosis and treatment models is increasing. Generative Adversarial …

The accelerating complexity and variety of medical imaging devices and methods have
outpaced the ability to evaluate and optimize their design and clinical use. This is a …

Breast cancer analysis implies that radiologists inspect mammograms to detect suspicious
breast lesions and identify mass tumors. Artificial intelligence techniques offer automatic …

Rationale and Objectives Generative adversarial networks (GANs) are deep learning
models aimed at generating fake realistic looking images. These novel models made a great …

Skin lesion datasets consist predominantly of normal samples with only a small percentage
of abnormal ones, giving rise to the class imbalance problem. Also, skin lesion images are …

Introduction This paper explores the potential of the StyleGAN model as an high-resolution
image generator for synthetic medical images. The possibility to generate sample patient …

The current COVID-19 pandemic, that has caused more than 100 million cases as well as
more than two million deaths worldwide, demands the development of fast and accurate …

Artificial intelligence techniques involving the use of artificial neural networks—that is, deep
learning techniques—are expected to have a major effect on radiology. Some of the most …

Early detection of the autosomal dominant polycystic kidney disease (ADPKD) is crucial as it
is one of the most common causes of end-stage renal disease (ESRD) and kidney failure …

Motivated by the lack of publicly available datasets of chest radiographs of positive patients
with coronavirus disease 2019 (COVID-19), we build the first-of-its-kind open dataset of …