Fitting density functions and diffusion tensors to three-dimensional drug transport within brain tissue

In the research on drug transport within brain tissue, typical data sets consist of a collection of volume integrals from various locations in the brain, with each datum measuring the total amount of drug in a sample of tissue. These samples contain medically useful information about the extent and orientation of the distribution of the drug, but extracting this information requires some mathematical analysis. The method of analysis presented here performs a nonlinear regression on the data to fit a multivariate density function (for example, a Gaussian density) to model such transport processes as diffusion and dispersion. The principal components of that density then characterize the size and shape of the distribution of drug.