scholarly journals Hybrid Multilevel Sparse Reconstruction for a Whole Domain Bioluminescence Tomography Using Adaptive Finite Element

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Jingjing Yu ◽  
Xiaowei He ◽  
Guohua Geng ◽  
Fang Liu ◽  
L. C. Jiao
Keyword(s):  
Finite Element ◽  
Adaptive Finite Element Method ◽  
Source Distribution ◽  
Adaptive Finite Element ◽  
Sparse Regularization ◽  
Bioluminescence Tomography ◽  
Reconstruction Scheme ◽  
Boundary Measurements ◽  
Ill Posed

Quantitative reconstruction of bioluminescent sources from boundary measurements is a challenging ill-posed inverse problem owing to the high degree of absorption and scattering of light through tissue. We present a hybrid multilevel reconstruction scheme by combining the ability of sparse regularization with the advantage of adaptive finite element method. In view of the characteristics of different discretization levels, two different inversion algorithms are employed on the initial coarse mesh and the succeeding ones to strike a balance between stability and efficiency. Numerical experiment results with a digital mouse model demonstrate that the proposed scheme can accurately localize and quantify source distribution while maintaining reconstruction stability and computational economy. The effectiveness of this hybrid reconstruction scheme is further confirmed within vivoexperiments.

scholarly journals Reconstruction Method for Optical Tomography Based on the Linearized Bregman Iteration with Sparse Regularization

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Chengcai Leng ◽  
Dongdong Yu ◽  
Shuang Zhang ◽  
Yu An ◽  
Yifang Hu
Keyword(s):  
A Priori ◽  
Optical Tomography ◽  
Reconstruction Method ◽  
Bregman Iteration ◽  
Sparse Regularization ◽  
Bioluminescence Tomography ◽  
Regularization Problem ◽  
Ill Posed ◽  
Linearized Bregman Iteration

Optical molecular imaging is a promising technique and has been widely used in physiology, and pathology at cellular and molecular levels, which includes different modalities such as bioluminescence tomography, fluorescence molecular tomography and Cerenkov luminescence tomography. The inverse problem is ill-posed for the above modalities, which cause a nonunique solution. In this paper, we propose an effective reconstruction method based on the linearized Bregman iterative algorithm with sparse regularization (LBSR) for reconstruction. Considering the sparsity characteristics of the reconstructed sources, the sparsity can be regarded as a kind ofa prioriinformation and sparse regularization is incorporated, which can accurately locate the position of the source. The linearized Bregman iteration method is exploited to minimize the sparse regularization problem so as to further achieve fast and accurate reconstruction results. Experimental results in a numerical simulation andin vivomouse demonstrate the effectiveness and potential of the proposed method.

scholarly journals Sparse Regularization-Based Reconstruction for Bioluminescence Tomography Using a Multilevel Adaptive Finite Element Method

2011 ◽  
Vol 2011 ◽  
pp. 1-11 ◽  
Author(s):  
Xiaowei He ◽  
Yanbin Hou ◽  
Duofang Chen ◽  
Yuchuan Jiang ◽  
Man Shen ◽  
...  
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Source Region ◽  
Quantitative Information ◽  
Adaptive Finite Element Method ◽  
Sparse Reconstruction ◽  
Reconstruction Method ◽  
Adaptive Finite Element ◽  
Bioluminescence Tomography ◽  
Element Method

Bioluminescence tomography (BLT) is a promising tool for studying physiological and pathological processes at cellular and molecular levels. In most clinical or preclinical practices, fine discretization is needed for recovering sources with acceptable resolution when solving BLT with finite element method (FEM). Nevertheless, uniformly fine meshes would cause large dataset and overfine meshes might aggravate the ill-posedness of BLT. Additionally, accurately quantitative information of density and power has not been simultaneously obtained so far. In this paper, we present a novel multilevel sparse reconstruction method based on adaptive FEM framework. In this method, permissible source region gradually reduces with adaptive local mesh refinement. By using sparse reconstruction withl1regularization on multilevel adaptive meshes, simultaneous recovery of density and power as well as accurate source location can be achieved. Experimental results for heterogeneous phantom and mouse atlas model demonstrate its effectiveness and potentiality in the application of quantitative BLT.

Three Dimensional Dynamic Analyses on Stroller Wheel with Shock Absorber

2013 ◽  
Vol 387 ◽  
pp. 159-163
Author(s):  
Yi Chern Hsieh ◽  
Minh Hai Doan ◽  
Chen Tai Chang
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Three Dimensional ◽  
Adaptive Finite Element Method ◽  
Adaptive Finite Element ◽  
The Road ◽  
Dimensional Finite Element ◽  
On The Road ◽  
Three Dimensional Finite Element ◽  
Element Method

We present the analyses of dynamics behaviors on a stroller wheel by three dimensional finite element method. The vibration of the wheel system causes by two different type barriers on the road as an experiment design to mimic the real road conditions. In addition to experiment analysis, we use two different packages to numerically simulate the wheel system dynamics activities. Some of the simulation results have good agreement with the experimental data in this research. Other interesting data will be measured and analyzed by us for future study and we will investigate them by using adaptive finite element method for increasing the precision of the computation results.

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