  This paper presents an efficient parallel radiative transfer-based
inverse-problem solver for time-domain optical tomography. The radiative
transfer equation provides a physically accurate model for the transport of
photons in biological tissue, but the high computational cost associated with
its solution has hindered its use in time-domain optical-tomography and other
areas. In this paper this problem is tackled by means of a number of
computational and modeling innovations, including 1) A spatial
parallel-decomposition strategy with perfect parallel scaling for the forward
and inverse problems of optical tomography on parallel computer systems; and,
2) A Multiple Staggered Source method (MSS) that solves the inverse transport
problem at a computational cost that is independent of the number of sources
employed, and which significantly accelerates the reconstruction of the optical
parameters: a six-fold MSS acceleration factor is demonstrated in this paper.
Finally, this contribution presents 3) An intuitive derivation of the
adjoint-based formulation for evaluation of functional gradients, including the
highly-relevant general Fresnel boundary conditions -- thus, in particular,
generalizing results previously available for vacuum boundary conditions.
Solutions of large and realistic 2D inverse problems are presented in this
paper, which were produced on a 256-core computer system. The combined
parallel/MSS acceleration approach reduced the required computing times by
several orders of magnitude, from months to a few hours.
