Native T1 maps at 3T has the capacity to accurately characterize chronic myocardial infarction (MI) territories, however it requires accurate identification of remote myocardium which in some cases is limited by image contrast between infarcted and remote myocardial territories. To overcome this limitation, we evaluated multiple automatic segmentation algorithms. Native T1 maps acquired in chronic MI patients were segmented using Gaussian Mixture Model, Otsu’s and K-means methods. K-means approach showed the best performance when compared to LGE. We conclude that K-means approach can accurately delineate MI territories.