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http://dx.doi.org/10.9718/JBER.2022.43.6.390

A Study on the Quantitative Evaluation Method of Quality Control using Ultrasound Phantom in Ultrasound Imaging System based on Artificial Intelligence  

Yeon Jin, Im (Korea Medical Institute)
Ho Seong, Hwang (Department of Medical Artificial Intelligent, Graduate School, Eulji University)
Dong Hyun, Kim (Machine Intelligence Convergence System, Eulji University)
Ho Chul, Kim (Department Department of Health Science, Graduate School, Eulji University)
Publication Information
Journal of Biomedical Engineering Research / v.43, no.6, 2022 , pp. 390-398 More about this Journal
Abstract
Ultrasound examination using ultrasound equipment is an ultrasound device that images human organs using sound waves and is used in various areas such as diagnosis, follow-up, and treatment of diseases. However, if the quality of ultrasound equipment is not guaranteed, the possibility of misdiagnosis increases, and the diagnosis rate decreases. Accordingly, The Korean Society of Radiology and Korea society of Ultrasound in Medicine presented guidelines for quality management of ultrasound equipment using ATS-539 phantom. The DenseNet201 classification algorithm shows 99.25% accuracy and 5.17% loss in the Dead Zone, 97.52% loss in Axial/Lateral Resolution, 96.98% accuracy and 20.64% loss in Sensitivity, 93.44% accuracy and 22.07% loss in the Gray scale and Dynamic Range. As a result, it is the best and is judged to be an algorithm that can be used for quantitative evaluation. Through this study, it can be seen that if quantitative evaluation using artificial intelligence is conducted in the qualitative evaluation item of ultrasonic equipment, the reliability of ultrasonic equipment can be increased with high accuracy.
Keywords
Ultrasound; Artificial intelligence; Quality control; Classification; Quantitative evaluation;
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Times Cited By KSCI : 2  (Citation Analysis)
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