Journal of Biomedical Engineering Research (대한의용생체공학회:의공학회지)

The Korean Society of Medical and Biological Engineering (대한의용생체공학회)
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A Study on the Quantitative Evaluation Method of Quality Control using Ultrasound Phantom in Ultrasound Imaging System based on Artificial Intelligence

인공지능을 활용한 초음파영상진단장치에서 초음파 팬텀 영상을 이용한 정도관리의 정량적 평가방법 연구

  • 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)
  • 임연진 (한국의학연구소) ;
  • 황호성 (을지대학교 일반대학원 의료인공지능학과) ;
  • 김동현 (을지대학교 인공지능 융합 시스템 연구실) ;
  • 김호철 (을지대학교 일반대학원 보건학과)
  • Received : 2022.11.07
  • Accepted : 2022.11.29
  • Published : 2022.12.31
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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.

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References

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