Automatic Contrast Enhancement with Differential Evolution for Leukemia Cell Identification

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

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

1 Cita (Scopus)

Resumen

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 $$99.83\%$$.

Idioma originalInglés
Título de la publicación alojadaPattern Recognition - 11th Mexican Conference, MCPR 2019, Proceedings
EditoresJesús Ariel Carrasco-Ochoa, José Francisco Martínez-Trinidad, José Arturo Olvera-López, Joaquín Salas
EditorialSpringer Verlag
Páginas282-291
Número de páginas10
ISBN (versión impresa)9783030210762
DOI
EstadoPublicada - 1 ene 2019
Evento11th Mexican Conference on Pattern Recognition, MCPR 2019 - Querétaro, México
Duración: 26 jun 201929 jun 2019

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen11524 LNCS
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia11th Mexican Conference on Pattern Recognition, MCPR 2019
País/TerritorioMéxico
CiudadQuerétaro
Período26/06/1929/06/19

Huella

Profundice en los temas de investigación de 'Automatic Contrast Enhancement with Differential Evolution for Leukemia Cell Identification'. En conjunto forman una huella única.

Citar esto