Artificial Intelligence for X-Ray and CT-Scan in Modern Healthcare

The applications of Artificial Intelligence (AI) for X-ray and CT-Scan image analysis using Convolutional neural network architectures, Generative adversarial networks, transfer learning, and data augmentation techniques are discussed. Currently, AI algorithms embedded on a mobile x-ray and CT-Scan devices for automated diagnosis, measurements, case prioritization, and quality control are most popular research area. More than 60,000 research articles have been published related to the use of deep learning in healthcare and related applications. Established architectures, such as ResNet-50 or DenseNet-161 (with 50 and 161 representing the number of layers within the respective neural network) are easy to use. Integration of the AI modules with the drug systems and the experts are the key issues of implementing AI systems in healthcare.