Symbolic Learning using Brain Programming for the Recognition of Leukemia Images

Rocio Ochoa-Montiel, Humberto Sossa, Gustavo Olague, Mariana Chan-Ley, José Menendez


In this work, we propose an approach of symbolic learning for the recognition of leukemia images. Image recognition for cancer detection is often a subjective problem due to different interpretations by experts of the medical area. Feature extraction is acritical step in image recognition, and current automatic approaches are unintelligible since they need to be adapted to different image domains. We propose the paradigm of brain programming as a symbolic learning approach to address aspects involved in the derivation of knowledge that allows us to recognize subtypes of leukemia in color images. Experimental results provide evidence that the multi-class recognition task is achieved through the solutions discovered from multiples runs of the bioinspired model.


Leukemia recognition, symbolic learning, brain programming, evolutionary computer vision

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