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 motion correction algorithm based on different feature extraction techniques and subsequent classification techniques. Based on several simulation results, we determined the optimal motion compensation parameters, the optimal feature number and tested different classification techniques. Our results have shown that motion compensation can improve in some cases classification results.© (2009) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.