| dc.description.abstract | The work within this thesis develops three-dimensional image reconstruction algorithm of diffuse optical tomography (DOT) system with arbitrary surface models for breast cancer detection. The image reconstruction algorithm of DOT is based on the diffusion equation, and involves both the forward problem and inverse reconstruction. The forward calculation solves the diffusion equation by using the finite element method (FEM) for calculating the distribution of transmitted light under the condition of presumed light source and optical coefficient (absorption and reduced scattering coefficients) of the model. The inverse calculation reconstructs the distribution of the optical coefficient by using Newton′s method to minimize the difference between theory and measured data. Due to ill-posed nature of the inverse problem, Tikhonov regularization is utilized to stabilize the reconstruction result.
In this thesis, different designated simulation cases, including different position of inclusion (an embedded synthetic tumor), size, and contrast ratio of absorption and reduced scattering coefficient of inclusion respect to background were used for verifying the results of forward problem (light intesity and phase shift of photon density Φ(r)) and developed reconstruction algorithm. For case under condition by using 80 mm diameter breast-like phantom as a geometry, tumor with diameter of 20 mm, located at x = 15 mm, y = 0 mm, and z = 40 mm. The same reduced scattering coefficient and different absorption coefficients were performed first, then the same absorption coefficient and different reduced scattering coefficients were employed thereafter. The evaluation results show that, the greater absorption coefficient, the greater light intesity differences between homogenous and inhomogeneous condition. On the other hand, the greater reduced scattering coefficient, the greater light intensity and phase shift differences between homogenous and inhomogeneous condition. They also show that, the reconstruction results with same reduced scattering coefficient and different absorption coefficients will lead to over estimation of absorption coefficient. On the other hand, under estimation is occured for reduce scattering coefficient. By acquiring the reconstruction results of same absorption coefficient and different reduced scattering coefficients, they indicate absorption coefficients will lead to significant over estimation if the contrast ratio of reduced scattering coefficient for inclusion and background is equal to 2. Moreover, under estimation is occurred for reduced scattering coefficient.
For breast model from MRI image (Magnetic Resonance Imaging)/NMR (Nuclear Magnetic Resonance) imaging with tumor embedded within the model had diameter of 20 mm, located at x = 0 mm, y = -15 mm, and z = 30 mm, the evaluation results demonstrate that, with same reduced scattering coefficient and different absorption coefficients will lead to over estimation of absorption coefficient. The greater absorption coefficient of inclusion in exact conditon, the greater over estimation of absorption coefficient for inclusion respect to background in reconstructed image. On the other hand, under estimation is occured for reduced scattering coefficient. In addition, the reconstruction results of same absorption coefficient and different reduced scattering coefficients. They indicate absorption coefficients will lead to over estimation if the contrast ratio of reduced scattering coefficient for inclusion and background is equal to 2.5. Futhermore, under estimation is occurred for reduced scattering coefficient.
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