We analyze the accuracy of atlas-based cartilage segmentation from isotropic T1ρ MRI and compare it to semi-automated "seed and blanket" method and manual segmentation (ground truth). Reference 3D cartilage masks were taken as the consensus of two human experts. For patella, our implementation of template matching yielded the root mean square volume measurement error RMSE of 0.66 cm3, with interclass correlation coefficient (ICC) = 0.765 and sufficient precision to detect the gender effect. Over two-fold improvement in accuracy, RMSE = 0.25 cm3 and ICC = 0.960 was achieved with a fast, semi-automated algorithm. Similar results hold for the accuracy of the average thickness of segmented masks.