Advertisement

The image reconstruction for fluorescence molecular tomography via a non-uniform mesh

  • Bin Wang
  • Pu Jiao
  • Huangjian YiEmail author
  • Xin Cao
  • Fengjun Zhao
  • Yuqing Hou
  • Xiaowei HeEmail author
Regular Paper
  • 16 Downloads

Abstract

As an optical molecular imaging modality, fluorescence molecular tomography (FMT) can monitor the activities of organisms in vivo at the molecular and cellular levels. However, the recovered image quality is affected by mesh voxel when the finite element method is utilized to recover the fluorescence probe. The target localization is likely to deviate from the actual target under the coarse mesh, but using the fine mesh will increase the number of unknowns, which makes the computational burden heavier and further aggravate the ill-posedness. To solve the problem, a reconstruction strategy using a non-uniform mesh for FMT is developed in this paper. The numerical experiment and physical experiment validated that the strategy is capable and effective for FMT.

Keywords

Optical molecular imaging Fluorescence molecular tomography Finite element method Non-uniform mesh 

Notes

Compliance with ethical standards

Conflict of interest

We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work, there is no professional or other personal interest of any nature or kind in any product, service and/or company that could be construed as influencing the position presented in, or the review of, the manuscript entitled “The image reconstruction for fluorescence molecular tomography via a non-uniform mesh”.

References

  1. 1.
    Ntziachristos, V., Tung, C.-H., Bremer, C., Weissleder, R.: Fluorescence molecular tomography resolves protease activity in vivo. Nat Med. 8(7), 757–761 (2002)CrossRefGoogle Scholar
  2. 2.
    Bai, J., Xu, Z.: Molecular Imaging: Fundamentals and Applications, pp. 185–216. Springer, Berlin (2013)CrossRefGoogle Scholar
  3. 3.
    Xu, C., Xin, W., Zhang, B., Fei, L., Luo, J., Jing, B.: Accelerated image reconstruction in fluorescence molecular tomography using dimension reduction. Biomed Opt Express. 4(1), 1–14 (2013)CrossRefGoogle Scholar
  4. 4.
    Vasilis, N., Schellenberger, E.A., Jorge, R., Doreen, Y., Edward, G., Alexei, B., Lee, J., Ralph, W.: Visualization of antitumor treatment by means of fluorescence molecular tomography with an annexin V-Cy5.5 conjugate. Proc Natl Acad Sci USA 101(33), 12294–12299 (2004)CrossRefGoogle Scholar
  5. 5.
    Dimarzio, C.A., Niedre, M.: Pre-clinical optical molecular imaging in the lung: technological challenges and future prospects. J Thorac Dis 4(6), 556–557 (2012)Google Scholar
  6. 6.
    Chen, D., Liang, J., Li, Y., Qiu, G.: A sparsity-constrained preconditioned Kaczmarz reconstruction method for fluorescence molecular tomography. BioMed Res Int 2016, Article ID: 4504161 (2016)Google Scholar
  7. 7.
    Lian, L., Deng, Y., Xie, W., Xu, G., Yang, X., Zhang, Z., Luo, Q.: Enhancement of the localization and quantitative performance of fluorescence molecular tomography by using linear nBorn method. Opt Express 25(3), 2063–2079 (2017)ADSCrossRefGoogle Scholar
  8. 8.
    Guven, M., Reilly-Raska, L., Zhou, L., Yazıcı, B.: Discretization error analysis and adaptive meshing algorithms for fluorescence diffuse optical tomography: Part I. IEEE Trans Med Imaging. 29(2), 217–229 (2010)CrossRefGoogle Scholar
  9. 9.
    Guven, M., Reilly-Raska, L., Zhou, L., Yazici, B.: Discretization error analysis and adaptive meshing algorithms for fluorescence diffuse optical tomography: Part II. IEEE Trans Med Imaging 29(2), 230–245 (2010)CrossRefGoogle Scholar
  10. 10.
    Zhou, L., Yazici, B.: Discretization error analysis and adaptive meshing algorithms for fluorescence diffuse optical tomography in the presence of measurement noise. IEEE Trans Image Process 20(4), 1094–1111 (2010)ADSMathSciNetCrossRefGoogle Scholar
  11. 11.
    Wang, D., Song, X.L., Bai, J.: Adaptive-mesh-based algorithm for fluorescence molecular tomography using an analytical solution. Opt Express. 15(15), 9722–9730 (2007)ADSCrossRefGoogle Scholar
  12. 12.
    Schulz, R.B., Angelique, A., Athanasios, S., Marcus, F., Eric, S., Marta, Z., Vasilis, N.: Hybrid system for simultaneous fluorescence and x-ray computed tomography. IEEE Trans Med Imaging 29(2), 465–473 (2009)CrossRefGoogle Scholar
  13. 13.
    Yi, H., Zhang, X., Peng, J., Zhao, F., Wang, X., Hou, Y., Chen, D., He, X.: Reconstruction for limited-projection fluorescence molecular tomography based on a double-mesh strategy. Biomed Res Int 2016, Article ID: 5682851 (2016)Google Scholar
  14. 14.
    Yi, H., Jiao, P., Li, X., Peng, J., He, X.: Three-way decision based reconstruction frame for fluorescence molecular tomography. J. Opt. Soc. Am. 35(11), 1814–1822 (2018)ADSCrossRefGoogle Scholar
  15. 15.
    Han, D., Tian, J., Zhu, S.P., Feng, J.C., Qin, C.G., Zhang, B., Yang, X.: A fast reconstruction algorithm for fluorescence molecular tomography with sparsity regularization. Opt. Express. 18(8), 8630–8646 (2010)ADSCrossRefGoogle Scholar
  16. 16.
    Xiaowei, H., Jimin, L., Xiaorui, W., Jingjing, Y., Xiaochao, Q., Xiaodong, W., Yanbin, H., Duofang, C., Fang, L., Jie, T.: Sparse reconstruction for quantitative bioluminescence tomography based on the incomplete variables truncated conjugate gradient method. Opt Express. 18(24), 24825–24841 (2010)CrossRefGoogle Scholar
  17. 17.
    Hou, Y., Hua, X., Xin, C., Zhang, H., Xuan, Q., He, X.: Single-view enhanced cerenkov luminescence tomography based on sparse bayesian learning. Acta Optica Sinica. 37(12), 298–308 (2017)Google Scholar
  18. 18.
    Guo, H., Hou, Y., He, X., Yu, J., Cheng, J., Xin, P.: Adaptive hp finite element method for fluorescence molecular tomography with simplified spherical harmonics approximation. J. Innov. Opt. Health Sci. 7(2), Article ID 1350057 (2014)CrossRefGoogle Scholar
  19. 19.
    Klose, A.D., Ntziachristos, V., Hielscher, A.H.: The inverse source problem based on the radiative transfer equation in optical molecular imaging. J. Comput. Phys. 202(1), 323–345 (2005)ADSCrossRefGoogle Scholar

Copyright information

© The Optical Society of Japan 2019

Authors and Affiliations

  1. 1.School of Information Sciences and TechnologyNorthwest UniversityXi’anChina

Personalised recommendations