Abstract: A radiation reduction system that includes a computer and an imaging device configured to provide an image of a subject during a medical procedure using electromagnetic radiation. A variety of inputs are accepted from the medical practitioner using the computer such as subject body type, weight, and the like. These user inputs are used by the computer to determine operating settings that are transmitted to the imaging device either manually, a wired connection or wirelessly. The calculated settings are useful to generate one or more medically useful images of the subject while significantly reducing the overall radiation exposure to the subject and/or the personnel and/or medical practitioner.

Abstract: Methods, systems, and apparatuses are described herein for using processes and machine learning techniques to optimize medical imaging processes to reduce inadvertent exposure to harmful radiation. A machine learning model may be trained to output recommended medical imaging device operating parameter settings. Available operating parameters of a medical imaging device may be determined, and patient data may be received. The patient data and the available operating parameters may be used as input to the trained machine learning model, which might output recommended operating parameter settings. In turn, this output in addition to other calculations might be used to transmit, to the medical imaging device, data that causes modification of the operating parameters of the medical imaging device. Metadata corresponding to one or more images captured by the medical imaging device may be received, and the trained machine learning model might be further trained based on that metadata.