Article - Artificial Intelligence and Imaging Optimization

In recent years, through its ability to collect and swiftly analyze huge volumes of data generated by imaging studies, artificial intelligence (AI) has been revolutionizing the practice of radiology. Throughout the field, applications leveraging AI are being used to improve diagnostic accuracy, imaging consistency, workflow efficiency, and patient care by automating many formerly tedious, time-consuming, and manually performed tasks. Traditional methods for implementing AI have relied primarily on machine-learning algorithms based on expert programming of predefined rules. More recent advances, however, have given rise to superior algorithms that learn through direct navigation of data to "recognize" potentially suspicious findings. These "deep learning" algorithms are advantageous because they operate with minimal human expert intervention, and instead collect and process data in raw form through the use of artificial neural networks.