About this Journal Submit a Manuscript Table of Contents
Advances in Artificial Neural Systems
Volume 2012 (2012), Article ID 919281, 8 pages
http://dx.doi.org/10.1155/2012/919281
Research Article

Selection of Spatiotemporal Features in Breast MRI to Differentiate between Malignant and Benign Small Lesions Using Computer-Aided Diagnosis

1Department of Computer Science, Technical University of Munich, 8574 Garching, Germany
2Department of Scientific Computing, Florida State University, Tallahassee, FL 32306-4120, USA
3Institute for Clinical Radiology, University of Munich, 81377 Munich, Germany
4Department of Electrical and Computer Engineering, FAMU/FSU College of Engineering, Tallahassee, FL 32310-6046, USA

Received 29 February 2012; Accepted 14 May 2012

Academic Editor: Juan Manuel Gorriz Saez

Copyright © 2012 F. Steinbruecker et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to Cite this Article

F. Steinbruecker, A. Meyer-Baese, C. Plant, T. Schlossbauer, and U. Meyer-Baese, “Selection of Spatiotemporal Features in Breast MRI to Differentiate between Malignant and Benign Small Lesions Using Computer-Aided Diagnosis,” Advances in Artificial Neural Systems, vol. 2012, Article ID 919281, 8 pages, 2012. doi:10.1155/2012/919281