Given the importance of myelin in brain structure and function, the advancement of MR-based myelin imaging techniques has drawn a great deal of attention. In this abstract we propose a statistical framework for analyzing myelin imaging, taking us one step closer to standardizing and industrializing MR-based myelin biomarkers. In a nutshell, we are computing Pearson correlation coefficients for scan-rescan reliability and taking their differences to determine if some myelin techniques are more reliable than others. We tested this framework in ex vivo dog spinal cord and found the differences between myelin metrics to be subtle, indicating that one metric can often serve as a surrogate for another.
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