Automatic Recognition of Leukemia AML Using Evolutionary Vision

Authors

  • Rocio Ochoa-Montiel Universidad Autónoma de Tlaxcala
  • Humberto Sossa Instituto Politécnico Nacional
  • Gustavo Olague Centro de Investigación Científica y de Educación Superior de Ensenada
  • Carlos Sanchez-López Universidad Autónoma de Tlaxcala

DOI:

https://doi.org/10.13053/cys-27-1-4536

Keywords:

Leukemia, automatic recognition, evolutionary vision

Abstract

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.

Author Biographies

Rocio Ochoa-Montiel, Universidad Autónoma de Tlaxcala

Facultad de Ciencias Basicas Ingeniería y Tecnología

Humberto Sossa, Instituto Politécnico Nacional

Centro de Investigacion en Computación

Gustavo Olague, Centro de Investigación Científica y de Educación Superior de Ensenada

EvoVision Laboratory

Carlos Sanchez-López, Universidad Autónoma de Tlaxcala

Facultad de Ciencias Basicas Ingeniería y Tecnología

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Published

2023-03-30

Issue

Vol. 27 No. 1 (2023): 27(1) 2023

Section

Articles of the Thematic Section

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