Imaging and learning in back-scattered light by artificial neural networks

Dumitru Iulian Nastac; Razvan Matei; Paul Dan Cristea; Manfred D. Kessler

doi:10.1117/12.469473

5 June 2002 Imaging and learning in back-scattered light by artificial neural networks

Dumitru Iulian Nastac, Razvan Matei, Paul Dan Cristea, Manfred D. Kessler

Proceedings Volume 4623, Functional Monitoring and Drug-Tissue Interaction; (2002) https://doi.org/10.1117/12.469473
Event: International Symposium on Biomedical Optics, 2002, San Jose, CA, United States

Abstract

The paper presents a new way to study the results obtained by back-scattering of light in tissue through artificial intelligence. The artificial neural networks' (ANN) ability to extract significant information from an initial set of data allows both an interpolation, in the a priori defined points, and an extrapolation outside of the range bordered by the extreme points from the initial training set. The data obtained from EMPHO Spectrophotometer were used for neural networks learning. Specific aspects related to the training procedure and parameter fitting are presented. The evaluation of the computing effort shows some way for future optimizations.

Citation Download Citation

Dumitru Iulian Nastac, Razvan Matei, Paul Dan Cristea, and Manfred D. Kessler "Imaging and learning in back-scattered light by artificial neural networks", Proc. SPIE 4623, Functional Monitoring and Drug-Tissue Interaction, (5 June 2002); https://doi.org/10.1117/12.469473

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