DOI QR코드

DOI QR Code

Improvement of Angiogram Quality Using by High Pass Filter

고역통과필터를 이용한 혈관조영상의 화질 개선

  • Received : 2014.06.30
  • Accepted : 2014.10.25
  • Published : 2014.10.30

Abstract

In this study, an image acquired by the DSA(Digital Subtraction Angiography) system that is configured to configure the algorithm for high pass filtering algorithm experiments to improve the quality of angiography methods proposed. high pass filter is a high-frequency components pass through the filter, blocking low-frequency components. Part of the boundary line and contour of the organ corresponds to the high-frequency component is a high-frequency component of a medical image. Therefore, the high pass filter is also used for detection of the boundary line, but is also used for the high frequency enhancement. It was able to be analyzed by the proposed algorithm, to improve the quality of the angiography. Found out that the expression of the target site stand out clearly. The quality of the DSA system proposed in the wrong diagnosis software can be used to reduce, it is possible to develop and will further improve the accuracy of the treatment.

본 연구에서는 DSA 장치에 의하여 획득된 영상을 고역 통과 필터링 알고리즘을 구성하여 구성된 알고리즘으로 실험을 하여 혈관조영상의 화질을 개선하는 방안을 제안하였다. 고역 통과 필터(High Pass Filter)는 고주파 성분은 통과시키고 저주파 성분은 차단하는 필터이다. 의료영상에서 고주파 성분은 장기(organ)의 윤곽이나 경계선 부분이 고주파 성분에 해당된다. 따라서 고역 통과 필터는 경계선 검출에도 쓰이지만 고역 강조를 위해서도 이용된다. 제시한 알고리즘으로 분석을 하여 혈관조영상의 화질을 개선할 수 있었다. 목적부위의 표현이 확연하게 두드러짐을 알 수 있었다. 제안된 방안을 이용한다면 DSA 시스템의 화질을 개선하는 소프트웨어에 적용하여 오진을 줄여주고 시술의 정확도를 더욱 높여 줄 수 있을 것이라 사료된다.

Keywords

References

  1. Deokmun Gwon, Sungsoo Kim, Youngkeun Kim other 17 people, Analog& Digital.PACS Medical Imaging Informatics, DAIHAK, pp.267, 2001.
  2. JeongPyo Lee, Jongyoeon Lee, Changho Hyun, Coin Recognition and Classification Using Digital Image Processing, JKΙΙS, Vol. 22, No. 1, pp. 7-11, 2012. https://doi.org/10.5391/JKIIS.2012.22.1.7
  3. Jung Hwan, Digital Radiographic Technology, JMK, 2003.
  4. Ioannis Pitas, Digital Image Processing Algorithms and Applications, Wiley-interscience, 2000.
  5. Xu Long, Nam-Ho Kim, Image Restoration for Edge Preserving in Mixed Noise Environment, JKIICE. Vol. 18, No. 3, 727-734 Mar. 2014. https://doi.org/10.6109/jkiice.2014.18.3.727
  6. Seungbong Hong, Woosuk Tae, Three Dimensional Multi-Modality Image Fusion and Other Advanced Image Techniques in Localizing Epileptic Focus, JKES. 2(2). pp.112-120, 1998.
  7. Sangbock Lee, Junhaeng Lee, Samual Lee, NamJin Kim, Gyehwan Jin, Digital medical image processing, pp. 37, 2006.
  8. Kisee Joo, Grid Pattern Segmentation Using High Pass Filter, The Journal of Korea navigation institute, v.11 no.1 = no.24, pp.59-63, 2007.
  9. SungHo Park, JoongJae Lee, GeunSoo Lee, GyeYoung Kim, Flexible Background-Texture Analysis for Coronary Artery Extraction Based on Digital Subtraction Angiography, Korea Information Processing Society Review, Vol. 12-B, No. 5, pp. 543-552, 2005. https://doi.org/10.3745/KIPSTB.2005.12B.5.543
  10. Junhaeng Lee, PSNR Evaluation of P Company DSA System between Server Display Monitor and Client Display Monitor, J. Korean Soc. Radiol., Vol. 8, No. 1, pp.43-49, 2014. https://doi.org/10.7742/jksr.2014.8.1.43

Cited by

  1. Image Quality Improvement in Computed Tomography by Using Anisotropic 2-Dimensional Diffusion Based Filter vol.10, pp.1, 2016, https://doi.org/10.7742/jksr.2016.10.1.45