Evaluation of healthy and infected cervical tissue using a LIFS system and a back-propagation neural network

Authors

  • A. Aparicio Castillo
  • J. M. de la Rosa Vázquez
  • P. A. Calva Chavarría
  • E. B. Franco López
  • R. Torres Manzo
  • R. Álvarez Dorantes
  • G. de la Rosa Gutiérrez
  • M. B. Romero Guadarrama

Abstract

 

Laser-Induced Fluorescence Spectroscopy (LIFS) is a technique that has been recently used to detect in vivo or in vitro cancer. The LIFS system has been used to analyze cervical tissue samples for histological evaluation. Because the fluorescence spectra are position and inter-probe dependent (albeit they were equally classified by histological evaluation) the relationship that exists in the data is complex. So, a back-propagation Artificial Neural Network is used to detect the relationships contained within them. The validation of the system was done with 5 different proves and a 100% classification coincidence between the neural network classification and a normal histological one was obtained. The LIFS-System works with a N2 laser of 5 µJ pulse energy (tFWHM = 3.8 ns at 337.1 nm wavelength) and spectra from 350 to 650 nm were processed and evaluated in a PC.

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Published

2006-12-06

How to Cite

Aparicio Castillo, A., de la Rosa Vázquez, J. M., Calva Chavarría, P. A., Franco López, E. B., Torres Manzo, R., Álvarez Dorantes, R., de la Rosa Gutiérrez, G., & Romero Guadarrama, M. B. (2006). Evaluation of healthy and infected cervical tissue using a LIFS system and a back-propagation neural network. Revista Mexicana De Ingenieria Biomedica, 27(2), 6. Retrieved from http://rmib.mx/index.php/rmib/article/view/357

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Research Articles

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