MEDICAL IMAGING SYSTEMS FOR REDUCING RADIATION EXPOSURE
案件概要
発明者
Phillip R. Kingma; Letrisha Weber
IPC分類
CPC分類
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.
原文(中国語)
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.
外部リソース