Korean Journal of Optics and Photonics (한국광학회지)

Optical Society of Korea (한국광학회)
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Impmvement of Inverse Fitting Algorinlm of Visible Reflectance Spectrum to Extract Skin Parameters

피부의 특성 추출을 위한 가시광선 반사 스펙트럼의 역 추적 최적화 알고리즘 개선

  • Choi, Seung-Ho (Department of Biomedical Engineering, Yonsei University) ;
  • Im, Chang-Hwan (Department of Biomedical Engineering, Yonsei University) ;
  • Jung, Byung-Jo (Department of Biomedical Engineering, Yonsei University)
  • 최승호 (연세대학교 보건과학대학 의공학부) ;
  • 임창환 (연세대학교 보건과학대학 의공학부) ;
  • 정병조 (연세대학교 보건과학대학 의공학부)
  • Published : 2007.06.25
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Abstract

In order to extract more accurate skin parameters, this study was focused on the improvement of the efficiency of a previous inverse fitting algorithm based on genetic algorithms. The algorithm provides the best fitting result of the diffusion approximation model to a VRS (visual reflectance spectroscopy) curve of skin. Simplex and wavelength selection methods were applied to the previous algorithm. Nine skin parameters were inversely extracted from the modeling studies. The revised inverse fitting algorithm was determined to produce an 83% reduction of computation time and a 0.64% reduction of sum of square error, compared to the previous algorithm. In conclusion, we confirmed that the new algorithm provides faster and more accurate solutions for the diffusion approximation model.

본 논문은 가시광선 반사 스펙트럼으로부터 피부조직의 광학적, 구조적 특성을 역 추출하는 알고리즘에 대한 연구를 다룬다. 본 연구에서는 유전알고리즘을 사용한 기존의 역 추적 최적화 알고리즘에 파장 선택법과 심플렉스법을 추가하여 알고리즘의 최적화 능력을 개선하였다. 파장 선택법은 기존 알고리즘에 사용된 135개의 파장 중 10개의 유효 파장만을 사용한 결과 계산시간이 83% 감소하였다. 심플렉스법을 사용해 유전알고리즘으로 얻은 근사적인 탐색 점으로부터 재 탐색을 수행하였고, 이를 통해 얻은 탐색 점의 SSE(sum of square error)는 기존 유전알고리즘 만으로 얻은 탐색 점이 가지는 SSE의 0.64%였다. 본 연구의 모델링 결과를 통해 개선된 알고리즘이 기존 알고리즘에 비해 빠르고 정확한 해를 찾는다는 것을 확인할 수 있었다.

Keywords

References

  1. E. Berardesca, P. H. Andersen, P. Bjerring, and H. I. Maibach, 'Erythema induced by organic-solvents in vivo evaluation of oxygenized and deoxygenized hemoglobin by reflectance spectroscopy,' Contact Dermatitis, vol. 27, pp. 8-11, 1992 https://doi.org/10.1111/j.1600-0536.1992.tb05190.x
  2. L. T. Norvang, E. J. Fiskerstrand, B. Badden, D. Grini, O. Standahl, T. F. Milner, M. W. Berns, J. S. Nikon, and L. O. Svassand, 'The influence of tissue parameters on visual reflectance spectra of portwine stains and normal skin,' Proc. SPIE, vol. 2623, pp. 2-14, 1995 https://doi.org/10.1117/12.230298
  3. I. V. Meglinski and S. J. Matcher, 'Quantitative assessment of skin layers absorption and skin reflectance spectra simulation in the visible and near-infrared spectral regions,' Physiol. Meas., vol. 23, pp. 741-753, 2002 https://doi.org/10.1088/0967-3334/23/4/312
  4. A. Ishimaru, Wave Propagation and Scattering in Random Media, Vol. 1 (Academic Press, New York, USA, 1978), pp. 175-190
  5. M. Keijzer, W. M. Star, and P, R. M. Storichi, 'Opticaldiffusion in layered media,' Applied Optics., vol. 27, pp. 1820-1824, 1988 https://doi.org/10.1364/AO.27.001820
  6. R. Zheng, J. A. Viator, B. Jung, L. O. Svasand, G. Aguilar, and J. S. Nelson, 'Determination of human skin optical properties from spectrophotometric measurement based on optimization by genetic algorithms,' J. Biomed. Opt. vol. 10, pp. 024030, 2003 https://doi.org/10.1117/1.1891147
  7. W. H. Press, B. P. Flannery, S. A. Teukolsky and W. T. Vetterling, Numerical Recipes in C: The Art of Scientific Computing, 2nd Ed (Cambridge University Press, 1992), pp. 408-411
  8. K. M. Case and P. F. Zweifel, Linear Transport Theory (Addison-Welsley Publishing Co. Reading, 1967)
  9. W. F. Cheong, S. A. Prahl, and A. J. Welch, 'A Review of the Optical Properties of Biological Tissues,' IEEE J. Quantum Elect., vol. 26, pp. 2166-2185, 1990 https://doi.org/10.1109/3.64354
  10. S. L. Jacques, See http://omlc.ogi.edu/spectra/melanin/ index.html
  11. S. L. Jacques, See http://omlc.ogi.edu/spectra/hemoglobin/ index.html
  12. 진강규, 유전알고리즘과 그 응용(교우사, 서울, 한국, 2002), pp. 149-213
  13. Q. Ding, G. W. Small, and M. A. Arnold, 'Genetic algorithm-based wavelength selection for the near-infrared determination of glucose in biological matrixes: initialization strategies and effects of spectral resolution,' Anal. Chem., vol. 70, pp. 4472-4479, 1998 https://doi.org/10.1021/ac980451q
  14. O. Lakmaker, J. W. Pickering and J. C. Martin, 'Modeling the color perception of port wine stains and its relation to the depth of laser coagulation blood vessels,' Laser. Surg. Med., vol. 13, pp. 219-226, 1993 https://doi.org/10.1002/lsm.1900130210
  15. J. S. Arora, Introduction to Optimum Design, (Academic Press, Orlando, Florida, USA, 1989), pp. 198-218

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