Image Reconstruction in Diffuse Optical Tomography
cortex mesh

Surface of a cortex mesh

photon density distribution

Boundary solution of photon density

Toast++ in DOT

Toast++ is a software suite for image reconstruction in diffuse optical tomography (DOT). It contains a forward solver module using the finite element method for simulating the propagation of light in highly scattering, inhomogeneous biological tissues, such as the brain.

The inverse solver module uses an iterative, model-based approach to reconstruct the unknown distributions of absorption and scattering coefficients in the volume of interest from boundary measurements of light transmission.

Toast++ consists of a set of libraries written in C++ for sparse linear algebra, finite element computation, and nonlinear image reconstruction. Several command line applications for forward modelling and inverse solution are included. Users who need additional functionality can write their own applications and link to the core Toast++ libraries.

In addition, Toast++ contains bindings for Matlab and Python. This provides a set of functions for accessing the Toast methods from within these scripting environments, without loss of performance. Using Toast++ from within Matlab or Python provides a user-friendly way for quickly adapting Toast to a specific reconstruction problem. It allows rapid prototyping, debugging and visualisation.

The Toast++ sources are distributed with a GPL license. In addition to the sources, binary distributions for various computing platforms can be downloaded.

Toast++ toolbox is being developed by Martin Schweiger and Simon Arridge at University College London.

If you use Toast++ in your work, please reference it with the following citation:

M. Schweiger and S. R. Arridge, The Toast++ software suite for forward and inverse modeling in optical tomography, J Biomed Opt (2014) [in press]