Two-dimensional shape-based diffuse optical tomography: methodology, silumation and pilot experiment

In this paper we apply the shape-based approach to diffuse optical tomography (DOT) reconstruction, which aims to simultaneously recover the smooth boundaries of the tissue regions and the constant coefficients within them. An advantage of shape-based solutions is the reduction of the unknown parameters, which is especially important for nonlinear ill-posed inverse problems. We introduce a Fourier series representation of the closed region boundaries and a boundary element method (BEM) for the forward model. For inverse problem the Levenberg-Marquardt optimization process is implemented here. The performance of the proposed method is evaluated by simulations at different noise levels and phantom experiment which is embedded a single cylinder target. We can get reasonable reconstruction from both Gauss noise and real noise in the experimental study. The results illuminate that the methodology is very promising and of global convergence, the boundaries and the optical coefficients can both be recovered with good accuracy from the noisy measurements.