  Scatter processes of photons lead to blurring of images produced by CT
(computed tomography) or CBCT (cone beam computed tomography) in the KV domain
or portal imaging in the MV domain (KV: kilovolt age, MV: megavoltage).
Multiple scatter is described by, at least, one Gaussian kernel. In various
situations, this approximation is crude, and we need two/three Gaussian kernels
to account for the long-range tails (Landau tails), which appear in the
Moli\`ere scatter of protons, energy straggling and electron capture of charged
particles passing through matter and Compton scatter of photons. The ideal
image (source function) is subjected to Gaussian convolutions to yield a
blurred image recorded by a detector array. The inverse problem is to obtain
the ideal source image from measured image. Deconvolution methods of linear
combinations of two/three Gaussian kernels with different parameters s0, s1, s2
can be derived via an inhomogeneous Fredholm integral equation of second kind
(IFIE2) and Liouville - Neumann series (LNS) to provide the source function
{\rho}. The determination of scatter parameter functions s0, s1, s2 can be best
determined by Monte-Carlo simulations. A particular advantage of this procedure
is given, if the scatter functions s0, s1, s2 are not constant and depend on
coordinates. This fact implies that the scatter functions can be calibrated
according to the electron density {\rho}electron provided by image
reconstructions. The convergence criterion of LNS can always be satisfied with
regard to the above mentioned cases. A generalization of the present theory is
given by an analysis of convolution problems based on the Dirac equation and
Fermi-Dirac statistics leading to Landau tails. This generalization is applied
to Bethe-Bloch equation (BBE) of charged particles to analyze electron capture.
The methodology can readily be extended to other disciplines of physics.
