The presence of disease results in the production of odors different from thehealthy state, which can be detected by mice. Each odorant generates a uniqueglomeruli activation pattern in the murine olfactory system. However, thesesignals differ spatially and temporally across mice and capturing them is labor-intensive. To optimize the process, glomeruli activation patterns for many odor-ants could be mapped from a reference animal imaged on all available odorants totarget animals imaged on a subset of odorants. In our initial approach to developthis method, we align the glomeruli activation patterns for 11 odorants between 2mice using the optimal transport Sinkhorn algorithm.