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28 April 2005 Multiple step algorithm for fluorescence-enhanced diffuse optical tomography
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A discussion on recent works on diffusive inverse problems is presented with a special focus on three-dimensional imaging methods and their application to small animal imaging by fluorescence-enhanced Diffuse Optical Tomography. A numerical approach using the Finite Element Method for handling problems modelled by elliptic coupled partial differential equations is justified by the complexity of the geometry of the system but is known to be time- and memory-consuming. The resolution of the adjoint problem considerably speeds up the treatment and allows a full 3D resolution. Nevertheless, because of the ill-posedness of the problem, the reconstruction scheme is sensitive to a priori knowledge on the parameters to be reconstructed. In this study, a multiple step, self-regularized, reconstruction algorithm for the spatial distribution of the fluorescent regions is presented. We introduce the prior knowledge of the regions of interest via a segmentation of the results performed with a first rough reconstruction of the fluorescent regions. The results are then refined along iterations of the segmentation/reconstruction scheme.
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A. Da Silva, A. Planat-Chretien, J.-M. Dinten, and A. Gliere "Multiple step algorithm for fluorescence-enhanced diffuse optical tomography", Proc. SPIE 5693, Optical Tomography and Spectroscopy of Tissue VI, (28 April 2005);

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