Comparison of imaging geometries for diffuse optical tomography of tissue

Images produced in six different geometries with diffuse optical tomography simulations of tissue have been compared using a finite element-based algo rithm with iterative refinement provided by the Newton-Raphson approach. Th e source-detector arrangements studied include (i) fan-beam tomography, (ii ) full reflectance and transmittance tomography, as well as (iii) sub-surfa ce imaging, where each of these three were examined in a circular and a fla t slab geometry. The algorithm can provide quantitatively accurate results for all of the tomographic geometries investigated under certain circumstan ces. For example, quantitatively accurate results occur with sub-surface im aging only when the object to be imaged is fully contained within the diffu se projections. In general the diffuse projections must sample all regions around the target to be characterized in order for the algorithm to recover quantitatively accurate results. Not only is it important to sample the wh ole space, but maximal angular sampling is required for optimal image recon struction. Geometries which do not maximize the possible sampling angles ca use more noise artifact in the reconstructed images. Preliminary simulation s using a mesh of the human brain confirm that optimal images are produced from circularly symmetric source-detector distributions, but that quantitat ively accurate images can be reconstructed even with a sub-surface imaging, although spatial resolution is modest. (C) 1999 Optical Society of America .