Journal of the Institute of Electronics and Information Engineers (전자공학회논문지)

The Institute of Electronics and Information Engineers (대한전자공학회)
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A Diagnosis Method of Basal Cell Carcinoma by Raman Spectra of Skin Tissue using NMF Algorithm

피부 조직의 라만 스펙트럼에서 NMF 알고리즘을 통한 기저 세포암 진단 방법

  • Received : 2013.02.25
  • Published : 2013.08.15
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Abstract

Basal cell carcinoma (BCC) is the most common skin cancer and its incidence is increasing rapidly. In this paper, we propose a diagnosis method of basal cell carcinoma by Raman spectra of skin tissue using the NMF(non-negative matrix factorization) algorithm. After preprocessing steps, measured Raman spectra is used classification experiments. The weight and the basis can be obtained in a simple matrix operation and a column vector of the matrix decompsed by the NMF. Linear combination of bases and weights, it is possible to approximate the average of Raman spectra. The classification method is to select the class which to minimize the root mean square of the difference of the linear combination and the objective spectrum. According to the experimental results, the proposed method shows the promising results to diagnosis BCC. In addition, it confirmed that the proposed method compared with the previous research result could be effectively applied in the analysis of the Raman spectra.

기저 세포암은 가장 일반적인 피부암이고 그 발병이 급속도로 증가하고 있다. 본 연구에서는 피부 조직에서 측정한 라만 스펙트럼에서 기저 세포암 진단을 위해 NMF(non-negative matrix factorization) 알고리즘을 사용하는 방법을 제안하였다. 측정된 라만 스펙트럼은 영역 선택과 정규화 등의 몇 가지 전처리 과정을 거쳐 분류 실험에 사용한다. 전처리 과정을 수행한 라만 스펙트럼은 NMF 알고리즘을 이용하여 분해된 행렬의 열벡터를 기저로 사용한다. 이 기저들을 선형 결합하여 각 클래스의 평균 스펙트럼에 근사하기 위한 가중치는 행렬 연산으로 결정한다. 분류 실험은 스펙트럼과 NMF에 의한 기저와 가중치의 선형 결합 스펙트럼의 차에 대한 제곱평균제곱근을 최소로 하는 클래스를 선택하는 것으로 수행한다. 기저 세포암의 진단을 위한 분류 실험에서 제안한 방법을 사용하는 경우가 약 99.1%의 평균 분류율로 이전의 BCC 진단에 사용한 방법보다 약 2-3% 정도의 향상된 성능을 보였다.

Keywords

References

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