Fluorescence spectral imaging for characterization of tissue based on multivariate statistical analysis.

@article{Qu2002FluorescenceSI,
  title={Fluorescence spectral imaging for characterization of tissue based on multivariate statistical analysis.},
  author={J. Qu and H. Chang and S. Xiong},
  journal={Journal of the Optical Society of America. A, Optics, image science, and vision},
  year={2002},
  volume={19 9},
  pages={
          1823-31
        }
}
  • J. Qu, H. Chang, S. Xiong
  • Published 2002
  • Computer Science, Medicine
  • Journal of the Optical Society of America. A, Optics, image science, and vision
A novel spectral imaging method for the classification of light-induced autofluorescence spectra based on principal component analysis (PCA), a multivariate statistical analysis technique commonly used for studying the statistical characteristics of spectral data, is proposed and investigated. A set of optical spectral filters related to the diagnostically relevant principal components is proposed to process autofluorescence signals optically and generate principal component score images of the… Expand
Investigation of Synchronous Fluorescence Method in Multicomponent Analysis in Tissue
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