Table of Contents
Advances in Artificial Neural Systems
Volume 2012, Article ID 808602, 10 pages
Research Article

Evaluation of a Nonrigid Motion Compensation Technique Based on Spatiotemporal Features for Small Lesion Detection in Breast MRI

1Department of Computer Science, Technical University of Munich, 85748 Garching, Germany
2Department of Scientific Computing, Florida State University, Tallahassee, FL 32306, USA
3Institute for Clinical Radiology, University of Munich, 81679 Munich, Germany

Received 17 March 2012; Accepted 21 May 2012

Academic Editor: Olivier Bastien

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.


Motion-induced artifacts represent a major problem in detection and diagnosis of breast cancer in dynamic contrast-enhanced magnetic resonance imaging. The goal of this paper is to evaluate the performance of a new nonrigid motion correction algorithm based on the optical flow method. For each of the small lesions, we extracted morphological and dynamical features describing both global and local shape, and kinetics behavior. In this paper, we compare the performance of each extracted feature set under consideration of several 2D or 3D motion compensation parameters for the differential diagnosis of enhancing lesions in breast MRI. Based on several simulation results, we determined the optimal motion compensation parameters. Our results have shown that motion compensation can improve the classification results. The results suggest that the computerized analysis system based on the non-rigid motion compensation technique and spatiotemporal features has the potential to increase the diagnostic accuracy of MRI mammography for small lesions and can be used as a basis for computer-aided diagnosis of breast cancer with MR mammography.