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Proceedings Paper

Analytical methods of microscopic fluorescence spectral imaging
Author(s): Jin Wang; ShiFu Fan; YouQuan Zhao
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Paper Abstract

Technology for fluorescence spectral imaging of microscopic has made significant strides advantages in the past several years. These advances have led to the enhanced choice of suitable diagnosis bases. Of course, fluorescence imaging can facilitate the study of disease at the molecular level in vivo. And this type of optical imaging has enabled real-time research to track cell movement, cell growth and other cell functions. With the addition of spectral imaging, fluorescence spectral imaging could complete a so-called 4-dimension imaging for the object. The investigator can obtain either the color imaging information or the information beyond it. The combination of both of them could show the relative completeness message. For evolution of software tools to deal with the resulting high-dimensionality datasets, it is necessary to find some effective and comparative reliable datasets analytical methods. In this paper, it also describes some quantitative fluorescence in tissue and addresses further applications of fluorescence spectral imaging. It includes MSE (Minimum Squared Error), PCA (Principal Components Analysis), ICA (Independent Component Analysis), FEA (Finite-Element Analysis), wavelet theory and their applications. They are useful in intact animals for disease detection, screening, diagnosis, treatment evaluation and drug development.

Paper Details

Date Published: 27 October 2006
PDF: 5 pages
Proc. SPIE 6047, Fourth International Conference on Photonics and Imaging in Biology and Medicine, 60472I (27 October 2006); doi: 10.1117/12.710958
Show Author Affiliations
Jin Wang, Tianjin Univ. (China)
ShiFu Fan, Tianjin Univ. (China)
YouQuan Zhao, Tianjin Univ. (China)


Published in SPIE Proceedings Vol. 6047:
Fourth International Conference on Photonics and Imaging in Biology and Medicine
Kexin Xu; Qingming Luo; Da Xing; Alexander V. Priezzhev; Valery V. Tuchin, Editor(s)

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