Automatic Contrast Enhancement with Differential Evolution for Leukemia Cell Identification

R. Ochoa-Montiel, O. Flores-Castillo, Humberto Sossa, Gustavo Olague

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Image enhancement techniques are needed to decrease the negative effects of blur or unwanted noise in image processing. In biomedical images, the quality of images is very important to achieve an adequate identification to detection or diagnosis purposes. This paper addresses the use of contrast enhancement to facilitate the identification of leukemia in blood cell images. Differential evolution algorithm is used to get parameters required to apply contrast enhancement specifically in the interest region in the image, which facilites the posterior identification of leukemic cells. Identification of leukemic cells is accomplished applying an edges extraction and dilatation. From this image, two types of neural networks are used to classify the cells like healthy or leukemic cells. In first experiment, a multilayer perceptron is trained with the backpropagation algorithm using geometric features extracted from image. While in the second, convolutional networks are used. A public dataset of 260 healthy and leukemic cell images, 130 for each type, is used. The proposed contrast enhancement technique shows satisfactory results when obtaining the interest region, facilitating the identification of leukemic cells without additional processing, like image segmentation. This way, computational resources are decreased. On the other hand, to identify the cell type, images are classified using neural networks achieving an average classification accuracy of $$99.83\%$$.

Original languageEnglish
Title of host publicationPattern Recognition - 11th Mexican Conference, MCPR 2019, Proceedings
EditorsJesús Ariel Carrasco-Ochoa, José Francisco Martínez-Trinidad, José Arturo Olvera-López, Joaquín Salas
PublisherSpringer Verlag
Pages282-291
Number of pages10
ISBN (Print)9783030210762
DOIs
StatePublished - 1 Jan 2019
Event11th Mexican Conference on Pattern Recognition, MCPR 2019 - Querétaro, Mexico
Duration: 26 Jun 201929 Jun 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11524 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th Mexican Conference on Pattern Recognition, MCPR 2019
CountryMexico
CityQuerétaro
Period26/06/1929/06/19

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Keywords

  • Contrast enhancement
  • Differential evolution
  • Leukemia cells

Cite this

Ochoa-Montiel, R., Flores-Castillo, O., Sossa, H., & Olague, G. (2019). Automatic Contrast Enhancement with Differential Evolution for Leukemia Cell Identification. In J. A. Carrasco-Ochoa, J. F. Martínez-Trinidad, J. A. Olvera-López, & J. Salas (Eds.), Pattern Recognition - 11th Mexican Conference, MCPR 2019, Proceedings (pp. 282-291). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11524 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-21077-9_26