Characteristics of Weight Function in a Steady-state Diffusion Optical Tomography

For practical use of image reconstruction in a steady-state diffusion optical tomography, a weight function is analytically derived in a linear perturbation approach. We show that the weight function at any voxel in the medium is given by a product of a sensitivity function at the voxel and a mean optical pathlength in the voxel, whose two parameters have independent behavior to each other. By use of Monte Carlo simulation, it is found that the mean path length is easily obtained without stochastic calculation by scattering coefficient in the medium. Weight function derived by the proposed method is in good agreement with exact solution based on Monte Carlo method.

[1]  J M Schmitt,et al.  Optimal probe geometry for near-infrared spectroscopy of biological tissue. , 1997, Applied optics.

[2]  Harry L. Graber,et al.  Near-infrared absorption imaging of dense scattering media by steady-state diffusion tomography , 1993, Photonics West - Lasers and Applications in Science and Engineering.

[3]  Carmen A Puliafito,et al.  Automated detection of retinal layer structures on optical coherence tomography images. , 2005, Optics express.

[4]  Vadim A. Markel,et al.  Experimental demonstration of an analytic method for image reconstruction in optical diffusion tomography with large data sets. , 2005, Optics letters.

[5]  I J Bigio,et al.  Measuring absorption coefficients in small volumes of highly scattering media: source-detector separations for which path lengths do not depend on scattering properties. , 1997, Applied optics.

[6]  A Ismaelli,et al.  Monte carlo procedure for investigating light propagation and imaging of highly scattering media. , 1998, Applied optics.

[7]  M. Miwa,et al.  Three-dimensional imaging of a tissuelike phantom by diffusion optical tomography. , 2001, Applied optics.

[8]  J G Fujimoto,et al.  Real-time, ultrahigh-resolution, optical coherence tomography with an all-fiber, femtosecond fiber laser continuum at 1.5 microm. , 2004, Optics letters.

[9]  J. Fujimoto,et al.  Optical Coherence Tomography , 1991 .

[10]  Photon path distribution in inhomogeneous turbid media: theoretical analysis and a method of calculation. , 2002, Journal of the Optical Society of America. A, Optics, image science, and vision.

[11]  D T Delpy,et al.  Near-infrared spectroscopy of the adult head: effect of scattering and absorbing obstructions in the cerebrospinal fluid layer on light distribution in the tissue. , 2000, Applied optics.

[12]  A. Hielscher,et al.  Three-dimensional optical tomography of hemodynamics in the human head. , 2001, Optics express.

[13]  R. Barbour,et al.  Influence of Systematic Errors in Reference States on Image Quality and on Stability of Derived Information for dc Optical Imaging. , 2001, Applied optics.

[14]  E. Watanabe,et al.  Spatial and temporal analysis of human motor activity using noninvasive NIR topography. , 1995, Medical physics.

[15]  B. Pogue,et al.  Spatially variant regularization improves diffuse optical tomography. , 1999, Applied optics.

[16]  K D Paulsen,et al.  Three-dimensional simulation of near-infrared diffusion in tissue: boundary condition and geometry analysis for finite-element image reconstruction. , 2001, Applied optics.

[17]  H Liu Unified analysis of the sensitivities of reflectance and path length to scattering variations in a diffusive medium. , 2001, Applied optics.