Volume 9, Issue 3 (lasers in medicine 2012)
lmj 2012, 9(3): 23-32 |
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Development of Forward Algorithms by using Finite Element Method with Fluorescent Molecular Tomography in Homogenouse Medium. lmj 2012; 9 (3) :23-32
URL: http://icml.ir/article-1-263-en.html
URL: http://icml.ir/article-1-263-en.html
Abstract: (9858 Views)
Background: Optical imaging is established as one of the modalities applied to molecular imaging studies. Molecular imaging can be used to visualization of molecular events in the cellular or sub cellular level. Among the different methods of optical imaging Fluorescent Molecular Tomography (FMT) is a non-invasive method for imaging the biological tissue at cellular level. The image reconstruction of FMT system has two main steps, Forward problem and invers problem. Forward problem simulate the light source distribution on surface of objects and the goal of Invers problem is the recovery of optical properties using measurement intensity at the surface of abject The goal of this study was developed of a fast algorithm for forward problem based on finite element method for 2-D geometry.
Material and Methods: Image reconstruction of optical tomography like FMT system include two steps which is described as forward and invers problem. The aim of present study was determination the fast algorithm for forward problem that is used in image reconstruction of FMT system. For this purpose diffusion equation was solved by using finite element method which is the fast, accurate and flexible technique. The air-tissue boundary was presented by Robin boundary condition. In order to generate simulated data, a 2-D circular mesh with linear triangular elements was used. The algorithm based on FEM to solve the diffusion approximation was developed and written in the MATLAB programming to measure the intensity on the nodal boundary pointes and evaluated by the open access software package that developed at the Darthmouth for NIR imaging
Results: The intensity of nodal boundary pointes was measured at each for tomography imaging. The FEM algorithm of diffusion approximation which was developed at this study was compared with NIRFAST. These results show the good agreement between the FEMDA code with NIRFAST. Although the error was low but the most of error is located near the source term. The results showed the significant correlational coefficients (R >0.95) which demonstrated the high accuracy of the algorithm.
Discussion and Conclusion: The FEDA algorithm shown that FEDA yields similar results to NIRFAST for the 2-D geometry. The results showed the significant correlation coefficients (R >0.95), which demonstrated the high accuracy of the algorithm. The algorithm which is designed and developed in this study is more fast, flexible and accurate than analytical method that has good agreement to NIRFAST results. The computation time was lower than analytical theory and useful for heterogonous medium with complex geometry.
Material and Methods: Image reconstruction of optical tomography like FMT system include two steps which is described as forward and invers problem. The aim of present study was determination the fast algorithm for forward problem that is used in image reconstruction of FMT system. For this purpose diffusion equation was solved by using finite element method which is the fast, accurate and flexible technique. The air-tissue boundary was presented by Robin boundary condition. In order to generate simulated data, a 2-D circular mesh with linear triangular elements was used. The algorithm based on FEM to solve the diffusion approximation was developed and written in the MATLAB programming to measure the intensity on the nodal boundary pointes and evaluated by the open access software package that developed at the Darthmouth for NIR imaging
Results: The intensity of nodal boundary pointes was measured at each for tomography imaging. The FEM algorithm of diffusion approximation which was developed at this study was compared with NIRFAST. These results show the good agreement between the FEMDA code with NIRFAST. Although the error was low but the most of error is located near the source term. The results showed the significant correlational coefficients (R >0.95) which demonstrated the high accuracy of the algorithm.
Discussion and Conclusion: The FEDA algorithm shown that FEDA yields similar results to NIRFAST for the 2-D geometry. The results showed the significant correlation coefficients (R >0.95), which demonstrated the high accuracy of the algorithm. The algorithm which is designed and developed in this study is more fast, flexible and accurate than analytical method that has good agreement to NIRFAST results. The computation time was lower than analytical theory and useful for heterogonous medium with complex geometry.
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