APPLICATIONS OF SIMILARITY MAPPING IN DYNAMIC MRI

Dynamic images are temporal sequences of images, where the intensities of certain regions of interest (ROI's) change with time, whereas anat omical structures remain stationary, In this paper, new applications o f dynamic image analysis, called similarity mapping, are reviewed. Sim ilarity mapping identifies regions in a dynamic image sequence accordi ng to their temporal similarity or dissimilarity with respect to a ref erence ROI. Pixels in the resulting similarity map whose temporal sequ ence is similar to the reference ROI have high correlation values and are bright, while those with low correlation values are dark, Therefor e, similarity mapping segments structures in a dynamic image sequence based on their temporal responses rather than spatial properties, This paper describes the abilities of similarity mapping to identify diffe rent image structures present in several dynamic MRI datasets with pot ential clinical value. We demonstrate that similarity mapping techniqu e has been successful in identifying the following structures: 1) rena l cortex and medulla, 2) activated areas of the brain during photic st imulation, 3) ischemia in the left coronary artery territory, 4) lung tumor, 5) tentorial meningioma, and 6) a region of focal ischemia in b rain.