Recent advances in deep learning have led to a promising performance in many medical
image analysis tasks. As the most commonly performed radiological exam, chest …

In recent years, medical images have significantly improved and facilitated diagnosis in
versatile tasks including classification of lung diseases, detection of nodules, brain tumor …

Abstract Machine Learning (ML) algorithms are used to train the machines to perform
various complicated tasks that begin to modify and improve with experiences. It has become …

Adversarial attacks pose a significant threat to deep learning models, specifically medical
images, as they can mislead models into making inaccurate predictions by introducing …

In the past years, deep neural networks (DNN) have become popular in many disciplines
such as computer vision (CV), natural language processing (NLP), etc. The evolution of …

The advent of the fourth industrial revolution along with developments in other emerging
technologies, such as Internet of Things, big data, artificial intelligence as well as cloud and …

Chest Radiograph or Chest X-ray (CXR) is a common, fast, non-invasive, relatively cheap
radiological examination method in medical sciences. CXRs can aid in diagnosing many …

In recent years, significant progress has been achieved using deep neural networks (DNNs)
in obtaining human-level performance on various long-standing tasks. With the increased …

Deep learning approaches have demonstrated great achievements in the field of computer-
aided medical image analysis, improving the precision of diagnosis across a range of …

Convolutional neural networks (CNNs) have been widely applied to medical images.
However, medical images are vulnerable to adversarial attacks by perturbations that are …