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Caractérisation de tissus biologiques par diffusion de la lumière : application au diagnostic du cancer

Abstract : Diffuse Optical Tomography (DOT) is a new medical imaging technique used to reconstruct the optical properties of biological tissues in order to detect cancerous tumors. However, this is an ill-posed and under-determined inverse problem. The work of this thesis deals with the resolution of this problem using the radiative transfer equation as a forward model of light propagation. The sensitivity analysis showed that the anisotropy factor g of the Henyey-Greenstein phase function is the most sensitive parameter of the forward model followed by the scattering coefficient µs and then the absorption coefficient µa. In a first step, a Gauss-Newton algorithm was implemented using the sensitivity functions. However, this algorithm allows to estimate a very limited number of the optical parameters (assumed to be constant in space). In a second step, a Quasi-Newton algorithm was developed to reconstruct the spatial distributions of the optical properties. The gradient of the objective function was efficiently computed by the adjoint method through the Lagrangian formalism with a Multi-frequency approach. The reconstructed images were obtained from simulated boundary data. The g factor was reconstructed as a new optical contrast agent in DOT and the crosstalk problem between this factor and µs has been studied. The results showed that the algorithm is efficient to reconstruct in 2D and 3D one or several tumor inclusions having different shapes. The quality of the reconstructed images was examined according to several parameters: the number of frequencies, the crosstalk, the contrast and the noise levels
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Submitted on : Thursday, March 29, 2018 - 5:28:08 PM
Last modification on : Friday, March 30, 2018 - 1:28:55 AM


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  • HAL Id : tel-01753866, version 1



Ahmad Addoum. Caractérisation de tissus biologiques par diffusion de la lumière : application au diagnostic du cancer. Thermique [physics.class-ph]. Université de Lorraine, 2018. Français. ⟨NNT : 2018LORR0013⟩. ⟨tel-01753866⟩



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