Determination of Thorax Exposure Factors in Conventional X-rays Imaging using the Artificial Neural Network Method

Donni Maulana Sipa, Jamrud Aminuddin

2019

Abstract

The application of artificial intelligence in the medical field is indispensable for providing optimum results. Conventional X-ray imaging is the fastest, most common and least expensive diagnostic imaging system available. However, an effective X-ray examination depends on the range of radiation given to the subject. The radiation from an X-ray primarily depends upon X-ray tube current (mA), tube voltage (kVp) and exposure time(s); these parameters define the dosage. X-ray radiation has a negative impact on the human body; this danger is not visible, but X-ray radiation can damage human cell tissue. This work aims to explore and analyze X-ray exposure parameter levels to the thorax with an artificial neural network, which helps to diagnose exposure of the tissue that is being irradiated. By entering distance, weight and height into the software, radiographers will get the optimum exposure factor settings for the patients’ thorax. The subjectivity of exposure factor settings from radiographers can be objective, and optimum exposure settings for patients can result in lower radiation with a good, detailed image, thereby reducing the impact of X-ray radiation.

Paper Citation

in Harvard Style

Sipa D. and Aminuddin J. (2019). Determination of Thorax Exposure Factors in Conventional X-rays Imaging using the Artificial Neural Network Method.In Proceedings of the 4th Annual International Conference and Exhibition on Indonesian Medical Education and Research Institute - Volume 1: The 4th ICE on IMERI, ISBN 978-989-758-433-6, pages 33-37. DOI: 10.5220/0009388100330037

in Bibtex Style

@conference{the 4th ice on imeri19,
author={Donni Maulana Sipa and Jamrud Aminuddin},
title={Determination of Thorax Exposure Factors in Conventional X-rays Imaging using the Artificial Neural Network Method},
booktitle={Proceedings of the 4th Annual International Conference and Exhibition on Indonesian Medical Education and Research Institute - Volume 1: The 4th ICE on IMERI,},
year={2019},
pages={33-37},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009388100330037},
isbn={978-989-758-433-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 4th Annual International Conference and Exhibition on Indonesian Medical Education and Research Institute - Volume 1: The 4th ICE on IMERI,
TI - Determination of Thorax Exposure Factors in Conventional X-rays Imaging using the Artificial Neural Network Method
SN - 978-989-758-433-6
AU - Sipa D.
AU - Aminuddin J.
PY - 2019
SP - 33
EP - 37
DO - 10.5220/0009388100330037