Artificial Intelligence-Based Data Analytics Techniques in Medical Imaging

In the medical field, AI is used for machine learning (ML) models to examine medical data and reveal insights for improving the health results of patients. Generally, medical imaging (MI) also called radiology which reconstructs many images in the body part for diagnostics and treatment. The main challenging task in MI is proper diagnosis and accurate detection of diseases. In this survey, MI-based Artificial Intelligence (AI), Big Data Analytics (BDA), ML, and Deep Learning (DL) were discussed. Also investigate the techniques and algorithms used in AI-based BDA in MI such as supervised learning, ML, unsupervised learning, and DL. Furthermore, the merits, demerits, advantages, disadvantages, and performance analysis of MI are discussed. The main contribution of the work is to analyze and surveys the AI-based BDA techniques and identifies the issues in medical imaging also provide proper solution for the issues. Finally, the performance assessment of the relevant topic is examined and provides the problem definition.