A Prediction Study on Bremsstrahlung Photon Flux of Tungsten as a Radiological Anode Material by using MCNPX and ANN Modeling

• Authors: H. Tekin , U. Kara , T. Manici , E. Altunsoy , T. Erguzel
• Languages of publication: EN

Abstracts

EN

Medical imaging is a technique that is mostly known as visual representations of the parts of body for clinical scans and analysis. In imaging process for medical purpose there take part radiologists, radiographers/radiology technicians, medical physicists, sonographers, nurses, and engineers. As an apart issue from the medical imaging devices, we can treat X-rays using devices such as radiography, computed tomography, fluoroscopy, dental cone-beam computed tomography, and mammography. All these devices are to perform X-ray using during medical imaging process. An X-ray beam is generated in a vacuum tube that is principally composed of an anode and a cathode material to produce X-ray beams, whose name is X-ray tube. The anode represents the component in which the X-ray beam produced that made from a piece of metal. For decades, tungsten (W) has been used as an anode material of various X-ray tubes. Tungsten has high atomic number and high melting point of 3370°C with low rate of volatilization. In this study, we performed Monte Carlo simulation for flux calculations of W target by using MCNP-X general purpose code and considered result as a data set for artificial neural network. It can be concluded that the results agreed well between Monte Carlo simulation and artificial neural network prediction.

Keywords

EN

artificial neural network; Monte Carlo; medical imaging

• Publisher: Institute of Physics, Polish Academy of Sciences
• Journal: Acta Physica Polonica A
• Year: 2017
• Volume: 132
• Issue: 3
• Pages: 433-435

Dates

published

2017-09

Contributors

author

H. Tekin

• Uskudar University, Vocational School of Health Services, Radiotherapy Department, Istanbul, Turkey
• Suleyman Demirel University, Vocational School of Health Service, Medical Imaging Department, Isparta, Turkey
• Uskudar University, Medical Radiation Research Center (USMERA), Istanbul, Turkey

author

U. Kara

• Suleyman Demirel University, Vocational School of Health Service, Medical Imaging Department, Isparta, Turkey

author

T. Manici

• Uskudar University, Medical Radiation Research Center (USMERA), Istanbul, Turkey

author

E. Altunsoy

• Uskudar University, Vocational School of Health Services, Medical Imaging Department, Istanbul, Turkey

author

T. Erguzel

• Uskudar University, Faculty of Engineering and Natural Sciences, Computer Engineering, Istanbul, Turkey

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Identifiers

DOI

10.12693/APhysPolA.132.433