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Li X.,Shenyang Ligong University | Tian X.,Shenyang Ligong University | Yang T.,Shenyang Ligong University | Yu T.,Karlsruhe University of Applied Sciences | Li S.,Solon High School
Progress in Biomedical Optics and Imaging - Proceedings of SPIE | Year: 2011

The technology of laser-induced auto-fluorescence spectroscopy was used on serum for the diagnosis of lung cancer. We use principal component analysis and discriminant analysis to analyze spectra, and got an accuracy of 88% in distinguishing lung cancer patients and healthy people. © 2011 SPIE-OSA.


Li X.,Shenyang Ligong University | Yang T.,Shenyang Ligong University | Yu T.,Karlsruhe University of Applied Sciences | Sun R.,Karlsruhe University of Applied Sciences | Li S.,Solon High School
Progress in Biomedical Optics and Imaging - Proceedings of SPIE | Year: 2011

In this paper, 514.5nm argon ion laser induced human serum Raman and auto-fluorescence spectra of normal, liver cirrhosis and liver cancer were measured and analyzed. The spectral differences between these three types of serums were observed and given brief explanations. Three parameters α, φ and Δλ were introduced to describe characteristics of each type of spectrum. Experimental results showed that these parameters might be applicable for discrimination of normal, liver cirrhosis and liver cancer, which will provide some reference values to explore the method of laser spectral diagnosis of cancer. © 2011 SPIE-OSA.


Li X.,Shenyang Ligong University | Yang T.,Shenyang Ligong University | Yu T.,Karlsruhe University of Applied Sciences | Li S.,Solon High School
Progress in Biomedical Optics and Imaging - Proceedings of SPIE | Year: 2011

Raman spectroscopy of tissues has been widely studied for the diagnosis of various cancers, but biofluids were seldom used as the analyte because of the low concentration. Herein, serum of 30 normal people, 46 colon cancer, and 44 rectum cancer patients were measured Raman spectra and analyzed. The information of Raman peaks (intensity and width) and that of the fluorescence background (baseline function coefficients) were selected as parameters for statistical analysis. Principal component regression (PCR) and partial least square regression (PLSR) were used on the selected parameters separately to see the performance of the parameters. PCR performed better than PLSR in our spectral data. Then linear discriminant analysis (LDA) was used on the principal components (PCs) of the two regression method on the selected parameters, and a diagnostic accuracy of 88% and 83% were obtained. The conclusion is that the selected features can maintain the information of original spectra well and Raman spectroscopy of serum has the potential for the diagnosis of colorectal cancer. © 2011 SPIE-OSA.


Yang T.,Shenyang Ligong University | Li X.,Shenyang Ligong University | Yu T.,Karlsruhe University of Applied Sciences | Sun R.,Karlsruhe University of Applied Sciences | Li S.,Solon High School
Optics InfoBase Conference Papers | Year: 2011

In this paper, Raman spectra of human serum were measured using Raman spectroscopy, then the spectra was analyzed by multivariate statistical methods of principal component analysis (PCA). Then linear discriminant analysis (LDA) was utilized to differentiate the loading score of different diseases as the diagnosing algorithm. Artificial neural network (ANN) was used for cross-validation. The diagnosis sensitivity and specificity by PCA-LDA are 88% and 79%, while that of the PCA-ANN are 89% and 95%. It can be seen that modern analyzing method is a useful tool for the analysis of serum spectra for diagnosing diseases. © 2011 SPIE-OSA.


Li X.,Shenyang Ligong University | Yang T.,Shenyang Ligong University | Li S.,Solon High School | Yu T.,Karlsruhe University of Applied Sciences
Progress in Biomedical Optics and Imaging - Proceedings of SPIE | Year: 2011

Surface enhanced Raman spectroscopy (SERS) has shown the advantage of detecting low concentration biofluids presently. Saliva SERS of 21 lung cancer patients and 22 normal people were measured and differentiated in this paper. Intensities of most peaks of lung cancer patients are weaker than that of normal people, some are stronger but with a small change rate. Those peaks were assigned to proteins and nucleic acids which indicate a corresponding decrease of substance in saliva. Principal component analysis (PCA) and linear discriminant analysis (LDA) were used to deduce and discriminate the two groups of data, resulted in accuracy, sensitivity, and specificity being 84%, 94%, and 81%, respectively. In conclusion, SERS of saliva has the ability of predicting lung cancer. © 2011 SPIE-OSA.

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