Medical imaging informatics plays an important role in the effectiveness of present-day radiology in healthcare systems. The advancement of artificial intelligence (AI), big data analytics, and the Internet of Things technologies greatly contribute to various healthcare applications. Artificial intelligence techniques have replaced human-based systems and provided systems where the prediction and diagnosis of healthcare diseases are quite accurate.

The development of reliable and accurate healthcare models is possible with the help of machine learning and deep learning technologies. Artificial intelligence has the power to solve many complex problems in medical imaging and is a technology that is supposed to decide the future of healthcare systems.

This Special Issue aims to highlight and address various issues in medical imaging and provide viable solutions utilizing artificial intelligence and big data tools. This Special Issue aims to cover all dimensions of medical imaging informatics discussing techniques, algorithms, tools, research practices, platforms, and applications. It also aims to show the future directions of the use of AI in medical systems. We welcome original research and review articles.

Potential topics include but are not limited to the following:

• Use of machine learning in medical imaging informatics
• Use of deep learning in medical imaging informatics
• Use of big data analytics in handling medical imaging informatics
• AI-based prediction of diseases in medical images
• Medical image classification and analytics using deep learning
• Automatic identification and extraction of information in medical images using natural language processing techniques
• Image segmentation in medical images using deep learning
• Image regeneration in medical images using deep learning
• Efficient evaluation of medical imaging datasets using big data analytics
• Internet of Things and medical imaging AI systems
• Privacy and security issues in medical imaging informatics
• Healthcare and medical images security
• Challenges and open issues in medical imaging informatics
• Future directions for use of deep learning and big data analytics in medical imaging informatics