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Proceedings Paper

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

Paper Details

Date Published: 5 June 2002
PDF: 10 pages
Proc. SPIE 4623, Functional Monitoring and Drug-Tissue Interaction, (5 June 2002); doi: 10.1117/12.469473
Show Author Affiliations
Dumitru Iulian Nastac, Institute of Physiology and Cardiology (Romania)
Razvan Matei, Nokia Networks Oy (Finland)
Paul Dan Cristea, Politechnica Univ. of Bucharest (Romania)
Manfred D. Kessler, Institute of Physiology and Cardiology (Germany)


Published in SPIE Proceedings Vol. 4623:
Functional Monitoring and Drug-Tissue Interaction
Manfred D. Kessler; Gerhard J. Mueller, Editor(s)

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