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Urine and Copro Recognition with Generalized Entropy and Neural Networks


Diana Calva, Miguel Angel Z??iga Garc?a, Carlos Duchanoy Mart?nez, Gerardo Reyes Salgado, Mario Lehman


Vol. 9  No. 4  pp. 173-179


We present the results for the study and classification of urine sediments and coproparasitoscopic specimens using neural networks. This method has the additional advantage of taking into account the internal geometry of certain structures and to classify them according to certain parameters such as fractal dimension and entropies. In this case we use Renyi and Tsallis entropies with order q. These results are introduced as information for a hierarchical neuronal network, and allows increasing the precision of the urine sediment and parasite microscopic determination.


Neural Networks, Urianalysis, Fecal Material Analysis, Automated Microscopy, pattern recognition, generalized entropy