tMCimg uses a Monte Carlo algorithm to model the transport
of photons through 3D highly volumes with spatially varying optical
properties and arbitrary boundary conditions. Both highly-scattering
tissues (e.g. white matter) and weakly scattering tissues (e.g. cerebral
spinal fluid) are supported. Using the clinical structural information
provided by MRI, X-Ray CT, or ultrasound, accurate solutions to the
photon migration forward problem are found in times ranging from minutes
to hours, depending on the optical properties and the computing resources
available.
tMCimg models the propagation of photons through the medium
using a Monte Carlo algorithm. For each photon an initial position and
orientation is specified in the input file. Assuming no boundaries are
encountered along the way, the photon advances one scattering length
(selected at random from an exponential distribution of possible lengths
characterized by the scattering coefficient \mu_s). After traveling
a full scattering length, the photon is first attenuated and then
it scatters into a new direction determined by a Heyney-Greenstein
distribution and the optical properties of the medium. The process
is then iterated until the photon either leaves the system or a user
configurable time-gate expires. By sampling many possible paths an
estimate of the overall photon distribution is built up (which is
asymptotically exact as the number of photons sampled increases).
This information is saved to disk for future use.
Proper documentation is still being written. For now, the source code is your best guide.