19 January 2001 Artificial neural networks analysis of laser-induced fluorescence spectra for characterization of peripheral vascular tissue
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Abstract
This study concerns the identification of the state of human peripheral vascular tissue by using Artificial Neural Networks. The fluorescence spectra, obtained by dual wavelength excitation of the tissue samples, were passed through a non-linear filter, based on a High Order Neural Network (HONN). Then a classical Multi-Layer Perceptron was employed to serve as the classifier of the feature vector. The above process resulted in the successful discrimination between normal and different types of pathological tissue.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
George Filippidis, George Filippidis, Giannis Zacharakis, Giannis Zacharakis, A. Katsamouris, A. Katsamouris, G. A. Rovithakis, G. A. Rovithakis, M. Maniadakis, M. Maniadakis, M. Zervakis, M. Zervakis, Theodore G. Papazoglou, Theodore G. Papazoglou, } "Artificial neural networks analysis of laser-induced fluorescence spectra for characterization of peripheral vascular tissue", Proc. SPIE 4158, Biomonitoring and Endoscopy Technologies, (19 January 2001); doi: 10.1117/12.413797; https://doi.org/10.1117/12.413797
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