Proposing Intelligent Approach to Predicting Air Kerma within Radiation Beams of Medical X-ray Imaging Systems
Abstract
:1. Introduction
- 1-.
- The determination of the air kerma by considering the heel effect;
- 2-.
- The determination of the air kerma using an artificial neural network, and the training of it with limited data at different angles, distances, and tube voltages;
- 3-.
- The calculation of the air kerma at a very high speed in comparison with previous works, and with a very high accuracy, using an artificial neural network;
- 4-.
- The determination of the air kerma for the tube voltages used in medical applications.
2. Methodology
2.1. Modeling Tube of Medical X-ray Imaging System
2.2. Artificial Neural Network
3. Results and Discussion
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Lu, Y.; Zheng, N.; Ye, M.; Zhu, Y.; Zhang, G.; Nazemi, E.; He, J. Proposing Intelligent Approach to Predicting Air Kerma within Radiation Beams of Medical X-ray Imaging Systems. Diagnostics 2023, 13, 190. https://doi.org/10.3390/diagnostics13020190
Lu Y, Zheng N, Ye M, Zhu Y, Zhang G, Nazemi E, He J. Proposing Intelligent Approach to Predicting Air Kerma within Radiation Beams of Medical X-ray Imaging Systems. Diagnostics. 2023; 13(2):190. https://doi.org/10.3390/diagnostics13020190
Chicago/Turabian StyleLu, Yanjie, Nan Zheng, Mingtao Ye, Yihao Zhu, Guodao Zhang, Ehsan Nazemi, and Jie He. 2023. "Proposing Intelligent Approach to Predicting Air Kerma within Radiation Beams of Medical X-ray Imaging Systems" Diagnostics 13, no. 2: 190. https://doi.org/10.3390/diagnostics13020190