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.
Acquisition of the optical structures within a biological body is critical to all the diffuse light imaging modalities, such as
diffuse optical tomography (DOT) and fluorescence molecular tomography (FMT). On an assumption of the optical
homogeneity within the organs, it can be cast as a shape-based DOT issue, which aims at simultaneously reconstructing
the boundary-describing parameters and optical properties of the disjoint domains of distinct tissue types. As the first
step to the solution of this issue, we propose here a continuous-wave mode, elliptic-region-based DOT scheme. The
methodology employs the boundary-element-method (BEM) solution to the diffusion equation as the forward model, and
solves a nonlinear inverse issue that seeks an optimal boundary configuration as well as the optical properties to
minimize the residual norm between measured and predicted data. The proposed scheme is validated using simulated
data for a cylindrical geometry embedding two absorption- and scattering-contrasting ellipses at different noise levels.
A linear generalized pulse spectrum technique for image reconstruction of fluorescence molecular tomography is
proposed. The algorithm employs a finite element method solution to the Laplace-transformed coupled diffusion
equations and can simultaneously reconstruct both fluorescent yield and lifetime images of fluorophores. The proposed
algorithm was validated using simulated data for 3D phantoms. We investigated the ability of the algorithm to
reconstruct the fluorescent yield and lifetime at different region, contrasted the imaging quality of different target
lifetime and proved the noise-robustness by using noisy data with different signal-to-noise ratio. The results show that
the approach accurately retrieves the position and shape of the target and prove the effectiveness of the methodology.
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