![]() Sahagian and Proussevitch, 1998), functional stereology has much greater practical application to non-spherical particles/objects because it is free of uncontrollable error propagation for all particles shapes. ![]() As compared to previously known 2D to 3D conversion methods (e.g. There is no limit to continuous distribution function types that could be used, such as Gaussian, Logistic, Weibull, Gamma, and others. A new stereological approach enables us to solve this problem by utilizing function minimization to find parameters of the distribution functions. ![]() Functional stereology applies known deconvolution techniques to obtain 3D size distributions from 2D cross-section data based on an assumption that both 2D and 3D statistics have known distribution functions with unknown parameters.
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