The acquisition of ECG-gated cine magnetic resonance images of the heart is routinely performed in apnea in order to suppress the motion artifacts caused by breathing. However, many factors including the 2D nature of the acquisition and the use of di erent beats to acquire the multiple-view cine images, cause this kind of artifacts to appear. This paper presents the qualitative evaluation of a method aiming to remove motion artifacts in multipleview cine images acquired on patients with hypertrophic cardiomyopathy diagnosis. The approach uses iconic registration to reduce for in-plane artifacts in long-axis-view image stacks and in-plane and out-of-plane motion artifacts in sort-axis-view image stack. Four similarity measures were evaluated: the normalized correlation, the normalized mutual information, the sum of absolute voxel di erences and the Slomka metric proposed by Slomka et al. The qualitative evaluation assessed the misalignment of di erent anatomical structures of the left ventricle as follows: the misalignment of the interventricular septum and the lateral wall for short-axis-view acquisitions and the misalignment between the short-axis-view image and long-axis-view images. Results showed the correction using the normalized correlation as the most appropriated with an 80% of success.