scholarly journals Image reconstruction in optical tomography

1997 ◽  
Vol 352 (1354) ◽  
pp. 717-726 ◽  
Author(s):  
Simon R. Arridge ◽  
Martin Schweiger

Optical tomography is a new medical imaging modality that is at the threshold of realization. A large amount of clinical work has shown the very real benefits that such a method could provide. At the same time a considerable effort has been put into theoretical studies of its probable success. At present there exist gaps between these two realms. In this paper we review some general approaches to inverse problems to set the context for optical tomography, defining both the terms forward problem and inverse problem . An essential requirement is to treat the problem in a nonlinear fashion, by using an iterative method. This in turn requires a convenient method of evaluating the forward problem, and its derivatives and variance. Photon transport models are described and methods for obtaining analytical and numerical solutions for the most commonly used ones are reviewed. The inverse problem is approached by classical gradient–based solution methods. In order to develop practical implementations of these methods, we discuss the important topic of photon measurement density functions , which represent the derivative of the forward problem. We show some results that represent the most complex and realistic simulations of optical tomography yet developed. We suggest, in particular, that both time–resolved, and intensity–modulated systems can reconstruct variations in both optical absorption and scattering, but that unmodulated, non–time–resolved systems are prone to severe artefact. We believe that optical tomography reconstruction methods can now be reliably applied to a wide variety of real clinical data. The expected resolution of the method is poor, meaning that it is unlikely that the type of high–resolution images seen in computed tomography or medical resonance imaging can ever be obtained. Nevertheless we strongly expect the functional nature of these images to have a high degree of clinical significance.

2011 ◽  
Vol 2011 ◽  
pp. 1-13 ◽  
Author(s):  
Michael Ghijsen ◽  
Yuting Lin ◽  
Mitchell Hsing ◽  
Orhan Nalcioglu ◽  
Gultekin Gulsen

Diffuse Optical Tomography (DOT) is an optical imaging modality that has various clinical applications. However, the spatial resolution and quantitative accuracy of DOT is poor due to strong photon scatting in biological tissue. Structurala prioriinformation from another high spatial resolution imaging modality such as Magnetic Resonance Imaging (MRI) has been demonstrated to significantly improve DOT accuracy. In addition, a contrast agent can be used to obtain differential absorption images of the lesion by using dynamic contrast enhanced DOT (DCE-DOT). This produces a relative absorption map that consists of subtracting a reconstructed baseline image from reconstructed images in which optical contrast is included. In this study, we investigated and compared different reconstruction methods and analysis approaches for regular endogenous DOT and DCE-DOT with and without MR anatomicala prioriinformation for arbitrarily-shaped objects. Our phantom and animal studies have shown that superior image quality and higher accuracy can be achieved using DCE-DOT together with MR structurala prioriinformation. Hence, implementation of a combined MRI-DOT system to image ICG enhancement can potentially be a promising tool for breast cancer imaging.


2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Jinping Tang ◽  
Bo Han ◽  
Weimin Han ◽  
Bo Bi ◽  
Li Li

Optical tomography is an emerging and important molecular imaging modality. The aim of optical tomography is to reconstruct optical properties of human tissues. In this paper, we focus on reconstructing the absorption coefficient based on the radiative transfer equation (RTE). It is an ill-posed parameter identification problem. Regularization methods have been broadly applied to reconstruct the optical coefficients, such as the total variation (TV) regularization and the L1 regularization. In order to better reconstruct the piecewise constant and sparse coefficient distributions, TV and L1 norms are combined as the regularization. The forward problem is discretized with the discontinuous Galerkin method on the spatial space and the finite element method on the angular space. The minimization problem is solved by a Jacobian-based Levenberg-Marquardt type method which is equipped with a split Bregman algorithms for the L1 regularization. We use the adjoint method to compute the Jacobian matrix which dramatically improves the computation efficiency. By comparing with the other imaging reconstruction methods based on TV and L1 regularizations, the simulation results show the validity and efficiency of the proposed method.


2018 ◽  
Vol 26 (2) ◽  
pp. 963 ◽  
Author(s):  
Mrwan Alayed ◽  
Mohamed A. Naser ◽  
Ishaq Aden-Ali ◽  
M. Jamal Deen

Author(s):  
Daniel Rabinovich ◽  
Dan Givoli ◽  
Shmuel Vigdergauz

A computational framework is developed for the detection of flaws in flexible structures. The framework is based on posing the detection problem as an inverse problem, which requires the solution of many forward problems. Each forward problem is associated with a known flaw; an appropriate cost functional evaluates the quality of each candidate flaw based on the solution of the corresponding forward problem. On the higher level, the inverse problem is solved by a global optimization algorithm. The performance of the computational framework is evaluated by considering the detectability of various types of flaws. In the present context detectability is defined by introducing a measure of the distance between the sought flaw and trial flaws in the space of the parameters characterizing the configuration of the flaw. The framework is applied to crack detection in flat membranes subjected to time-harmonic and transient excitations. The detectability of cracks is compared for these two cases.


2008 ◽  
Author(s):  
Feng Gao ◽  
Limin Zhang ◽  
Huiyuan He ◽  
Huijuan Zhao ◽  
Jingying Jiang ◽  
...  

2014 ◽  
Vol 986-987 ◽  
pp. 1418-1421
Author(s):  
Jun Shan Li

In this paper, we propose a meshless method for solving the mathematical model concerning the leakage problem when the pressure is tested in the gas pipeline. The method of radial basis function (RBF) can be used for solving partial differential equation by writing the solution in the form of linear combination of radius basis functions, that is, when integrating the definite conditions, one can find the combination coefficients and then the numerical solution. The leak problem is a kind of inverse problem that is focused by many engineers or mathematical researchers. The strength of the leak can find easily by the additional conditions and the numerical solutions.


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