Efficient Luminosity Enhancement in Human Brain Images using Pulse-Coupled Neural Networks

Authors

  • Kevin S. Aguilar Domínguez Tecnológico Nacional de México, CENIDET
  • Manuel Mejía Lavalle Tecnológico Nacional de México, CENIDET
  • Juan Humberto Sossa Azuela Instituto Politécnico Nacional, Centro de Investigación en Computación

DOI:

https://doi.org/10.13053/cys-1-1-3187

Keywords:

Medical image enhancement, artificial neural networks, intersection cortical model, pulsed-coupled neural networks

Abstract

Digital images are widely used in the medicine area but these could be degraded by several factors. The images affected in its luminosity generate a problem for its correct analysis, since they have a short dynamic range and low contrast. The need to obtain good quality images and the tendency to increase the resolution of images, require new techniques to solve this problem in less time, that´s why there is a need to looking for paradigms that would can take advantage of parallel computing such as Pulsed-Coupled Artificial Neural Networks. In this work, two methods based on the Intersection Cortical Model are proposed and implemented to enhance the luminosity in medical human brain image. Experiments shown that the proposed models are highly competitive.

Downloads

Published

2020-03-25

Issue

Vol. 24 No. 1 (2020): 24(1)2020

Section

Articles

License 

Hereby I transfer exclusively to the Journal "Computación y 
Sistemas", published by the Computing Research Center (CIC-IPN),
the Copyright of the aforementioned paper. I also accept that these 
rights will not be transferred to any other publication, in any other 
format, language or other existing means of developing.
I certify that the paper has not been previously disclosed or simultaneo
usly submitted to any other publication, and that it does not contain 
material whose publication would violate the Copyright or other 
proprietary rights of any person, company or institution. I certify that 
I have the permission from the institution or company where I work or 
study to publish this work.
The representative author accepts the responsibility for the publication
of this paper on behalf of each and every one of the authors. 
This transfer is subject to the following conditions:
  • The authors retain all ownership rights (such as patent rights) of this work, except for the publishing rights transferred to the CIC, through this document.
  • Authors retain the right to publish the work in whole or in part in any book they are the authors or publishers. They can also make use of this work in conferences, courses, personal web pages, and so on.
  • Authors may include working as part of his thesis, for non-profit distribution only.