Application of MAP and MLP Classifier on Raman Spectral Data for Classification of Liver Disease

라만 스펙트럼에서 간 질병 분류를 위한 MAP과 MLP 적용 연구

  • 박아론 (전남대학교 전자컴퓨터공학부) ;
  • 백성준 (전남대학교 전자컴퓨터공학부) ;
  • 양병흠 (전남대학교 전자컴퓨터공학부) ;
  • 나승유 (전남대학교 전자컴퓨터공학부)
  • Published : 2009.02.28


In this paper, we evaluated the performance of the automatic classifier applied for the discrimination of acute alcoholic liver injury and chronic liver fibrosis. The classifier uses the discriminant peaks of the preprocessed Raman spectrum as a feature set. In preprocessing step, we subtract baseline and apply Savitzky-Golay smoothing filter which is known to be useful at preserving peaks. After identifying discriminant peaks from the spectra, we carried out the classification experiments using MAP and neural networks. According to the experimental results, the classifier shows the promising results to diagnosis alcoholic liver injury and chronic liver fibrosis. Classification results over 80% means that the peaks used as a feature set is useful for diagnosing liver disease.


Acute Alcoholic Liver Injury;Ethanol-induced Chronic Liver Fibrosis;Liver Disease;Micro-Raman Spectra;Pattern Recognition


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