Development of Medical Image Quality Assessment Tool Based on Chest X-ray


KIPS Transactions on Software and Data Engineering, Vol. 12, No. 6, pp. 243-250, Jun. 2023
https://doi.org/10.3745/KTSDE.2023.12.6.243,   PDF Download:
Keywords: Chest X-ray, quality assessment, Deep Learning, Machine Learning
Abstract

Chest X-ray is radiological examination for xeamining the lungs and haert, and is particularly widely used for diagnosing lung disease. Since the quality of these chest X-rays can affect the doctor's diagnosis, the process of evaluating the quality must necessarily go through. This process can involve the subjectivity of radiologists and is manual, so it takes a lot of time and csot. Therefore, in this paper, based on the chest X-ray quality assessment guidelines used in clinical settings, we propose a tool that automates the five quality assessments of artificial shadow, coverage, patient posture, inspiratory level, and permeability. The proposed tool reduces the time and cost required for quality judgment, and can be further utilized in the pre-processing process of selecting high-quality learning data for the development of a learning model for diagnosing chest lesions.


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Cite this article
[IEEE Style]
G. Nam, D. Yoo, Y. Kim, J. Sun, J. Lee, "Development of Medical Image Quality Assessment Tool Based on Chest X-ray," KIPS Transactions on Software and Data Engineering, vol. 12, no. 6, pp. 243-250, 2023. DOI: https://doi.org/10.3745/KTSDE.2023.12.6.243.

[ACM Style]
Gi-Hyeon Nam, Dong-Yeon Yoo, Yang-Gon Kim, Joo-Sung Sun, and Jung-Won Lee. 2023. Development of Medical Image Quality Assessment Tool Based on Chest X-ray. KIPS Transactions on Software and Data Engineering, 12, 6, (2023), 243-250. DOI: https://doi.org/10.3745/KTSDE.2023.12.6.243.