Abstract
Reconstruction algorithms for diffuse optical tomography (DOT) and bioluminescence tomography (BLT) have been developed based on diffusion theory. The algorithms numerically solve the diffusion equation using the finite element method. The direct measurements of the uncalibrated light fluence rates by a camera are used for the reconstructions. The DOT is self-calibrated by using all possible pairs of transmission images obtained with external sources along with the relative values of the simulated data and the calculated Jacobian. The reconstruction is done in the relative domain with the cancelation of any geometrical or optical factors. The transmission measurements for the DOT are used for calibrating the bioluminescence measurements at each wavelength and then a normalized system of equations is built up which is self-calibrated for the BLT. The algorithms have been applied to a three dimensional model of the mouse (MOBY) segmented into tissue regions which are assumed to have uniform optical properties. The DOT uses the direct method for calculating the Jacobian. The BLT uses a reduced space of eigenvectors of the Green's function with iterative shrinking of the permissible source region. The reconstruction results of the DOT and BLT algorithms show good agreement with the actual values when using either absolute or relative data. Even a small calibration error causes significant degradation of the reconstructions based on absolute data.
Highlights
Bioluminescence imaging (BLI) is a noninvasive technique that can monitor biological processes at a molecular level and visualize disease progression and response to treatment [1,2,3,4]
Many different strategies have been proposed for Bioluminescence tomography (BLT) [10,11,12,13,14,15,16,17,18] but, in general, three components are necessary: a forward model of light propagation from the internal source to the animal surface, a calibration of the camera that links the image to the emittance, and a reconstruction algorithm, usually iterative, that estimates the source distribution that minimizes the difference between the observed images and those calculated by application of the forward model
In previous papers [25,26] we have described a strategy whereby this information can be obtained by diffuse optical tomography (DOT)
Summary
Bioluminescence imaging (BLI) is a noninvasive technique that can monitor biological processes at a molecular level and visualize disease progression and response to treatment [1,2,3,4]. Many different strategies have been proposed for BLT [10,11,12,13,14,15,16,17,18] but, in general, three components are necessary: a forward model of light propagation from the internal source to the animal surface, a calibration of the camera that links the image (e.g. counts per pixel) to the emittance (optical power per unit area), and a reconstruction algorithm, usually iterative, that estimates the source distribution that minimizes the difference between the observed images and those calculated by application of the forward model. Transmission images acquired with external fiber optics sources and the BLI camera can be used to reconstruct the optical properties which, in turn, are used in the BLT algorithm. Received 13 Jul 2012; revised 3 Oct 2012; accepted 9 Oct 2012; published 11 Oct 2012 1 November 2012 / Vol 3, No 11 / BIOMEDICAL OPTICS EXPRESS 2796 by example that the relative method outperforms the absolute method if the calibration process is imperfect
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