ABSTRACT
The attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR) was employed to acquire the infrared spectra of Radix Bupleuri and its unofficial varieties: the root of Bupleurum smithii Wolff and the root of Bupleurum bicaule Helm. The infrared spectra and spectra of Fourier self-deconvolution (FSD), discrete wavelet transform (DWT), and probability neural network (PNN) of these species were analyzed. By the method of FSD, there were conspicuous differences of the infrared absorption peak intensity of different types between Radix Bupleuri and its unofficial varieties. But it is hard to tell the differences between the root of Bupleurum smithii Wolff and the root of Bupleurum bicaule. The differences could be shown more clearly when the DWT was used. The research result shows that by the DWT technology it is easier to identify Radix Bupleuri from its unofficial varieties the root of Bupleurum smithii Wolff and the root of Bupleurum bicaule.
ABSTRACT
Sprague-Dawley (SD) rats' normal and abnormal pancreatic tissues are determined directly by attenuated total reflectance Fourier transform infrared (ATR-FT-IR) spectroscopy method. In order to diagnose earlier stage of SD rats pancreatic cancer rate with FT-IR, a novel method of extraction of FT-IR feature using discrete wavelet transformation (DWT) analysis and classification with the probability neural network (PNN) was developed. The differences between normal pancreatic and abnormal samples were identified by PNN based on the indices of 4 feature variants. When error goal was 0.01, the total correct rates of pancreatic early carcinoma and advanced carcinoma were 98% and 100%, respectively. It was practical to apply PNN on the basis of ATR-FT-IR to identify abnormal tissues. The research result shows the feasibility of establishing the models with FT-IR-DWT-PNN method to identify normal pancreatic tissues, early carcinoma tissues, and advanced carcinoma tissues.
