Open access peer-reviewed chapter

A Dialectical Method to Classify Alzheimer\'s Magnetic Resonance Images

By Wellington Pinheiro dos Santos, Francisco Marcos de Assis, Ricardo Emmanuel de Souza, Priscilla Batista Mendes, Henrique Specht de Souza Monteiro and Havana Diogo Alves

Published: October 1st 2009

DOI: 10.5772/9609

Downloaded: 1136

© 2009 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike-3.0 License, which permits use, distribution and reproduction for non-commercial purposes, provided the original is properly cited and derivative works building on this content are distributed under the same license.

How to cite and reference

Link to this chapter Copy to clipboard

Cite this chapter Copy to clipboard

Wellington Pinheiro dos Santos, Francisco Marcos de Assis, Ricardo Emmanuel de Souza, Priscilla Batista Mendes, Henrique Specht de Souza Monteiro and Havana Diogo Alves (October 1st 2009). A Dialectical Method to Classify Alzheimer\'s Magnetic Resonance Images, Evolutionary Computation Wellington Santos, IntechOpen, DOI: 10.5772/9609. Available from:

Embed this chapter on your site Copy to clipboard

<iframe src="http://www.intechopen.com/embed/evolutionary-computation/a-dialectical-method-to-classify-alzheimer-s-magnetic-resonance-images" />

Embed this code snippet in the HTML of your website to show this chapter

chapter statistics

1136total chapter downloads

More statistics for editors and authors

Login to your personal dashboard for more detailed statistics on your publications.

Access personal reporting

Related Content

This Book

Next chapter

Simultaneous Topology, Shape and Sizing Optimisation of Skeletal Structures Using Multiobjective Evolutionary Algorithms

By Chaid Noilublao and Sujin Bureerat

Related Book

First chapter

Novel Binary Particle Swarm Optimization

By Mojtaba Ahmadieh Khanesar, Hassan Tavakoli, Mohammad Teshnehlab and Mahdi Aliyari Shoorehdeli

We are IntechOpen, the world's leading publisher of Open Access books. Built by scientists, for scientists. Our readership spans scientists, professors, researchers, librarians, and students, as well as business professionals. We share our knowledge and peer-reveiwed research papers with libraries, scientific and engineering societies, and also work with corporate R&D departments and government entities.

+3,350 Open Access Books

+57,400 Citations in Web of Science

+107,500 IntechOpen Authors and Academic Editors

+560,000 Unique visitors per month

More about us