Journal of Korea Multimedia Society (한국멀티미디어학회논문지)

Korea Multimedia Society (한국멀티미디어학회)
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A New Software for Quantitative Measurement of Strabismus based on Digital Image

디지털 영상 기반 정량적인 사시각 측정을 위한 새로운 소프트웨어

  • 김태윤 (국립암센터 융합기술연구부 의공학연구과) ;
  • 서상신 (국립암센터 융합기술연구부 의공학연구과) ;
  • 김영재 (국립암센터 융합기술연구부 의공학연구과) ;
  • 양희경 (서울대학교 안과학교실, 분당서울대학교병원 안과) ;
  • 황정민 (서울대학교 안과학교실, 분당서울대학교병원 안과) ;
  • 김광기 (국립암센터 융합기술연구부 의공학연구과)
  • Received : 2012.02.13
  • Accepted : 2012.03.13
  • Published : 2012.05.31
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Abstract

Various methods for measuring strabismus have been developed and used in clinical diagnosis. However, most of them are based on the visual inspection by clinicians. For this reason, there is a high possibility of subjective evaluation in clinical decisions and they are only useful for cooperative patients. Therefore, the development of a more objective and reproducible method for measuring strabismus is needed. In this paper, we introduce a new software to complement the limitations of previous diagnostic methods. Firstly, we simply obtained facial images of patients and performed several preprocessing steps based on the spherical RGB color model with them. Then, the measurement of strabismus was performed automatically by using our 3D eye model and mathematical algorithm. To evaluate the validity of our software, we performed statistical correlation analysis of the results of the proposed method and the Krimsky test by two clinicians for ten patients. The coefficients of correlation for two clinicians were very high, 0.955 and 0.969, respectively. The coefficient of correlation between two clinicians also showed 0.968. We found a statistically significant correlation between two methods from our results. The newly developed software showed a possibility that it can be used as an alternative or effective assistant tool of previous diagnostic methods for strabismus.

사시 진단을 위해 임상에서는 다양한 사시각 측정 방법들이 개발되어 이용되어 왔다. 그러나 기존 방법들은 대부분 육안 검사에 의해 이루어지므로 사용자의 주관적인 판단이 개입할 가능성이 크며 협조적인 대상에 대해서만 측정이 용이하다는 단점이 있다. 따라서 보다 이를 보완할 수 있는 객관적이고 신뢰성 있는 사시각 측정 방법의 개발이 필요하다. 본 논문에서는 임상 측정 방법의 문제점들을 보완할 수 있는 컴퓨터 기반의 새로운 자동 사시각 측정 소프트웨어의 개발을 소개한다. 먼저 간단하게 촬영된 환자의 전안부 영상을 획득하고 구형 RGB 모델을 이용하여 전처리를 수행하였다. 이후 새롭게 개발된 3차원 안구모델과 수학적인 측정 알고리즘을 이용하여 사시각 측정이 자동적으로 이루어지도록 하였다. 유효성 평가를 위해 10명의 환자 데이터를 대상으로 두 명의 검사자가 임상 측정 방법 중의 하나인 크림스키 테스트 방법을 통해 측정한 결과와 개발 소프트웨어를 이용하여 측정한 결과를 비교하였다. 그 결과, 두 명의 검사자의 상관계수는 각각 0.955, 0.969로 나타났으며, 두 검사자 간의 상관계수는 0.968로 나타나 객관성과 재현성이 매우 높음을 확인하였다. 향후 기존 사시진단 검사 방법들의 보조 수단이나 새로운 대안으로써 폭넓게 활용될 수 있을 것으로 기대한다.

Keywords

References

  1. M.H. Goldbaum, M. Smithline, T.A. Poole, and H.A. Lincoff, "Geometric Analysis of Radial Buckling," American Journal of Ophthalmology, Vol.79, No.6, pp. 958-965, 1975. https://doi.org/10.1016/0002-9394(75)90678-9
  2. P. Riddell, L. Hainline, and I. Abramov, "Calibration of the Hirschberg Test in Human Infants," Investigative Ophthalmology & Visual Science, Vol.35, No.2, pp. 538-543, 1994.
  3. E. Krimsky, "The Binocular Examination of the Young Child," American J ournal of Ophthalmology," Vol.26, No.1, pp. 624-625, 1943.
  4. J. Felius, K.G. Locke, M.A. Hussein, D.R. Stager Jr., and D.R. Stager Sr., "Photographic Assessment of Changes in Torsional Strabisumus," Proceeding of the 35th Annual Meeting of the American Association for Pediatric Ophthalmology and Strabismus, pp. 17-21, 2009.
  5. J.M. Miller, H.L. Hall, J. Greivenkamp, and D.L. Guyton, "Quantification of the Brückner Test for Strabismus," Investigative Ophthalmology & Visual Science, Vol.36, No.5, pp. 897-905, 1995.
  6. Y. Watanabe, T. Kezuka, K. Harasawa, M. Usui, H. Yaguchi, and S. Shioiri, "A New Method for Assessing Motion-in-deph Perception in Strabismic Patients," British Journal of Ophthalmology, Vol.92, No.1, pp. 47-50, 2008. https://doi.org/10.1136/bjo.2007.117507
  7. L. Wang and D. Yu, "A Digital Diagnosis Instrument of Hess Screen for Paralytic Strabismus," Proceeding of the 1st International Conference on Bioinformatics and Biomedical Engineering(ICBBE 2007), pp. 1234-1237, 2007.
  8. M. Koch, S. Priglinger, R. Hoerantner, and T. Haslwanter, "Computer-Assisted Dosage Calculation for Strabismus Therapy in Myopic Patients," Acta Ophthalmologica, Vol.86, No.1, pp. 53-57, 2008. https://doi.org/10.1111/j.1600-0420.2007.00997.x
  9. M.W. Quick and R.G. Boothe, "A Photographic Technique for Measuring Horizontal and Vertical Eye Alignment Throughout the Field of Gaze," Investigative Ophthalmology & Visual Science, Vol.33, No.1, pp. 234-236, 1992.
  10. J.M. Miller, M. Mellinger, J.E. Greivenkemp, and K. Simons, "Videographic Hirschberg Measurement of Simulated Strabismic Deviations," Investigative Ophthalmology & Visual Science, Vol.34, No.11, pp. 3220-3229, 1993.
  11. S. Haseve, H. Ohtsuki, Y. Tadokoro, M. Okano, and T. Furuse, "The Reliability of a Video- Enhanced Hirschberg Test under Clinical Conditions," Investigative Ophthalmology & Visual Science, Vol.36, No.13, pp. 2678-2685, 1995.
  12. P.M. Riddell, L. Hainline, and I. Abramov, "Calibration of the Hirschberg Test in Human Infants," Investigative Ophthalmology & Visual Science, Vol.35, No.2, pp. 538-543, 1995.
  13. D. Model, M. Eizenman, and V. Sturm, "Fixation- free Assessment of the Hirschberg ratio," Investigative Ophthalmology & Visual Science, Vol.51, No.8, pp. 4035-4039, 2010. https://doi.org/10.1167/iovs.09-5014
  14. R.M. Potdar, A. Mishra, and S. Yadav, "Real Time Squint Eye Detection," International J ournal of Engineering and Advanced Technology, Vol.1, No.2, pp. 111-114, 2011.
  15. S.H. Han, T.H Yoo, and J.B Lee, "Digitized Videographic Measurement of Strabismic Angle," Journal of Korean Ophthalmology Society, Vol.39, No.4, pp. 118-123, 1998.
  16. D. Model and M. Eizenman, "An Automated Hirschberg Test for Infants," IEEE Transactions on Biomedical Engineering, Vol.58, No. 1, pp. 103-109, 2011 https://doi.org/10.1109/TBME.2010.2085000
  17. J.D.S. de Almeida, A.C. Silva, A.C. de Paiva, and J.A.M. Texeira, "Computational Methodology for Automatic Detection of Strabismus in Digital Images Through Hirschberg Test," Computers in Biology and Medicine, Vol.42, No.1, pp. 135-146, 2012. https://doi.org/10.1016/j.compbiomed.2011.11.001
  18. R.C. Gonzalez and R.E. Woods, Digital Image Processing 2nd Ed., Prentice-Hall, New Jersey, 2002.
  19. R.A. Johnson and D.W. Wichern, Applied Multivariate Statistical Analysis 5th Ed., Prentice-Hall, New Jersey, 2002.
  20. K. Sun and H. Wang, "A Composite Method to Extract Eye Contour," Affective Computing and Intelligent Interaction, Lecture Notes in Computer Science, Vol.3784, No.1, pp. 112-118, 2005.
  21. N. Funabki, M. Isogai, T. Higashino, and M. Oda, "An Eye-Contour Extraction Algorithm from Face Image Using Deformable Template matching," Memoirs of the Faculty of Engineering, Okayama University, Vol.40, No.1, pp. 78-82, 2006.
  22. Z. Hammal, and A. Caplier, "Eye and Eyebrows Parametric Models for Automatic Segmentation," Proceeding of the 6th IEEE Southwest Symposium on Image Analysis and Interpretation, pp. 138-141, LIS, Grenoble, 28-30, 2004.
  23. 이응주, "복합 칼라모델과 얼굴 특징자를 이용한 실시간 얼굴 검출 추적과 기울어진 얼굴보정 시스템," 멀티미디어학회논문지, 제9권, 제4호, pp. 470-481, 2006.
  24. H.K. Yang, S.B. Han, J.M. Hwang, Y.J. Kim, C.B. Jeong, and K.G. Kim, "Assessment of Binocular Alignment using The Three-dimensional Strabismus Photo Analyzer," British Journal of Ophthalmology, Vol.96, No.1, pp. 78-82, 2012. https://doi.org/10.1136/bjophthalmol-2011-300305

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