Proceedings of the IEEK Conference (대한전자공학회:학술대회논문집)

The Institute of Electronics and Information Engineers (대한전자공학회)
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Feature Extraction of Basal Cell Carcinoma with Decision Tree

결정 트리를 이용한 기저 세포암 특징 추출

  • Park, Aa-Ron (The School of Electronics and Computer Engineering Chonnam National University) ;
  • Baek, Seong-Joon (The School of Electronics and Computer Engineering Chonnam National University) ;
  • Won, Yong-Gwan (The School of Electronics and Computer Engineering Chonnam National University) ;
  • Kim, Dong-Kook (The School of Electronics and Computer Engineering Chonnam National University)
  • 박아론 (전남대학교 전자컴퓨터공학부) ;
  • 백성준 (전남대학교 전자컴퓨터공학부) ;
  • 원용관 (전남대학교 전자컴퓨터공학부) ;
  • 김동국 (전남대학교 전자컴퓨터공학부)
  • Published : 2006.06.21
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Abstract

In this study, we examined all peaks of confocal Raman spectra as peaks are the most important features for discrimination between basal cell carcinoma (BCC) and normal tissue (NOR). 14 peaks were extracted from these peaks using decision tree. For dimension reduction, frequently selected 4 peaks were chosen. They are located at 1014, 1095, 1439, $1523cm^{-1}$. These peaks were used as an input feature of the multilayer perceptron networks (MLP). According to the experimental results, MLP gave classification error rate of about 6.5%.

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