Complex Relationship Between Artificial Intelligence and CT Radiation Dose

Concerns over need for CT radiation dose optimization and reduction led to improved scanner efficiency and introduction of several reconstruction techniques and image processing-based software. The latest technologies use artificial intelligence (AI) for CT dose optimization and image quality improvement. While CT dose optimization has and can benefit from AI, variations in scanner technologies, reconstruction methods, and scan protocols can lead to substantial variations in radiation doses and image quality across and within different scanners. These variations in turn can influence performance of AI algorithms being deployed for tasks such as detection, segmentation, characterization, and quantification. We review the complex relationship between AI and CT radiation dose. (c) 2021 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Automated summary

Concerns over the need for optimizing and reducing CT radiation dose have led to the introduction of artificial intelligence (AI) technologies for CT dose optimization and image quality improvement. However, variations in scanner technologies, reconstruction methods, and scan protocols can result in substantial differences in radiation doses and image quality, which can in turn affect the performance of AI algorithms used for various tasks.