Vol. 4, No. 3, 2011

Download this article
Download this article For screen
For printing
Recent Issues

Volume 11
Issue 3, 361–540
Issue 2, 181–359
Issue 1, 1–179

Volume 10, 5 issues

Volume 9, 5 issues

Volume 8, 5 issues

Volume 7, 6 issues

Volume 6, 4 issues

Volume 5, 4 issues

Volume 4, 4 issues

Volume 3, 4 issues

Volume 2, 5 issues

Volume 1, 2 issues

The Journal
About the Journal
Subscriptions
Editorial Board
Editors’ Addresses
Editors’ Interests
Scientific Advantages
Submission Guidelines
Submission Form
Ethics Statement
Editorial Login
Author Index
Coming Soon
Contacts
 
ISSN: 1944-4184 (e-only)
ISSN: 1944-4176 (print)
An implementation of scatter search to train neural networks for brain lesion recognition

Jeffrey Larson and Francis Newman

Vol. 4 (2011), No. 3, 203–211
Abstract

In recent years, the use of computer aided diagnosis (CAD) has achieved acceptance in mammography and other areas. To facilitate automated detection of brain abnormalities, we propose a novel method for quickly training neural networks to classify brain images. Our method outperforms traditional neural network training methods by achieving a better balance between classification accuracy and training time.

Keywords
computer-aided diagnosis, scatter search, artificial neural networks, health care, diagnosis
Mathematical Subject Classification 2000
Primary: 90C59, 92B20
Secondary: 90C90, 92C50
Milestones
Received: 16 February 2010
Revised: 4 October 2010
Accepted: 11 November 2011
Published: 13 March 2012

Communicated by Kenneth S. Berenhaut
Authors
Jeffrey Larson
University of Colorado Denver
Department of Mathematical and Statistical Sciences
Campus Box 170
P.O. Box 173364
Denver, CO 80217-3364
United States
Francis Newman
University of Colorado Denver
Department of Radiation Oncology
1665 Aurora Court
Box F-706
Aurora, CO 80045
United States