Journal of the Institute of Electronics Engineers of Korea SC (전자공학회논문지SC)

The Institute of Electronics and Information Engineers (대한전자공학회)
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A Study to Apply the Neural Networks for Improvement of X-Ray Chest Image

흉부 X-Ray 영상개선을 위한 신경망 적용에 관한 연구

  • Lee, Ju-Won (Dept. of Electronics Eng., Gyeongsang National University) ;
  • Lee, Han-Wook (Dept. of Electronics Eng., Gyeongsang National University) ;
  • Lee, Jong-Hoe (Dept. of Electronics Eng., Gyeongsang National University) ;
  • Shin, Tae-Min (Dept. of Electronics Eng., Gyeongsang National University) ;
  • Kim Young-Il (Dept. of Electronics Eng., Gyeongsang National University) ;
  • Lee, Gun-Ki (Dept. of Electronics Eng., Gyeongsang National University)
  • Published : 2000.01.01
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Abstract

Recently, X-ray chest rediography is showing a tendency to take an image of digital radiography so as to diagnose the pathology of chest in a usual. When the radiologist observes the chest image derived from digital radiography system on the monitor, he feels difficult to find out the pathological pattern because the quality of chest radiography is unequal. It takes amount of time to adjust the proper image for diagnosis. Therefore, we propose the method of the chest image equalization using neural networks and provide the compared result with histogram equalization method.

흉부의 병변을 진단하기 위해 주로 사용되고 있는 흉부 X-선 촬영은 최근 컴퓨터 기술의 발달에 힘입어 디지털화 되고 있다. 디지털화된 흉부 영상을 방사선과 전문의가 모니터 상에서 관찰할 때 흉부 영상의 품질이 고르지 못하여 병변을 검출하기가 어려울 뿐만 아니라 이로 인하여 많은 진단 시간이 소요된다. 따라서 본 연구에서는 디지털 흉부 영상을 개선하기 위해 신경망을 이용하여 흉부 X-선 영상의 등화 방법을 제안하고 그 결과를 히스토그램 등화 방법과 비교하여 제시하였다.

Keywords

References

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