If I get this right...
Linear diffusion you can calculate by straightforward convolution with a Gaussian kernel, and that operation should commute with the integration along the lines-of-sight your imaging system does. If you start doing non-linear diffusion this will no longer be true - you would not get the same result if you first did a non-linear diffusion of the 3-D object and then imaged that, as if you first imaged the 3-D object and then did non-linear diffusion on that. So it depends on what type of diffusion you do. This is resting on the fact that the diffusion is done with a Gaussian kernel and that those are separable. This means that you can separate the diffusion perpendicular to and along the lines-of-sight.
HTH
