Carotid surgery is a frequent act corresponding to 15 to 20 thousands operations per year in France. Cerebral perfusion has to be tracked before and after carotid surgery. In this paper, a diagnosis support using quality metrics is proposed to detect vascular lesions on MR images. Our key stake is to provide a detection tool mimicking the human visual system behavior during the visual inspection. Relevant Human Visual System (HVS) properties should be integrated in our lesion detection method, which must be robust to common distortions in medical images. Our goal is twofold: to help the neuroradiologist to perform its task better and faster but also to provide a way to reduce the risk of bias in image analysis. Objective quality metrics (OQM) are methods whose goal is to predict the perceived quality. In this work, we use Objective Quality Metrics to detect perceivable differences between pairs of images.