Abstract: The tissue type classification is presented using the neural networks. The multi-spectral images of
uterine cervix were segmented using self-organizing Kohonen maps and k-means algorithm. Then, the
classification of tissue types from computed segments was made using the cascade neural network, back
propagating neural network, and RBF network. The basics of neural networks were briefly explained. The results
were presented and analyzed, based on which, the conclusions were made.
Keywords: neural networks, decision making, intellectual systems, segmentation.
ACM Classification Keywords: I.2.1 Applications and Expert Systems - Medicine and science
Link:
THE ANALYSIS OF NEURAL NETWORKS’ PERFORMANCE FOR MEDICAL IMAGE
CLASSIFICATION
Kateryna Malyshevska
http://www.foibg.com/ijicp/vol01/ijicp01-02-p11.pdf
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