Automatic Recognition of Leukemia AML Using Evolutionary Vision

Rocio Ochoa-Montiel, Humberto Sossa, Gustavo Olague, Carlos Sanchez-López


In this work, an evolutionary vision approach is used for the automatic recognition of AML leukemia images. Unlike common approaches using convolutional neural networks, in the presented model the feature extraction process is transparent. Moreover, the structure of the obtained solutions is amenable to interpretation by a human user, which is a significant advantage over automatic recognition approaches based on deep neural networks. Experimental results show that the evolutionary vision approach can obtain satisfactory results on the AML leukemia recognition problem.


Leukemia, automatic recognition, evolutionary vision

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