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A permissible region strategy for fluorescence molecular tomography

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Abstract

A large-scale fluorescence measurement captured by non-contact fluorescence molecular tomography imaging system is utilized to reconstruct the three-dimensional distribution of fluorescent probe in small animals. However, this makes the computational burden heavier and restricts the capacity of this technique. In general, the extracting area of interest is a universal method of increasing the effectiveness of the reconstruction. Hence, this study proposed permissible region extraction strategy by means of the node with the maximum energy at each projection. Simulation experiment and physical experiment demonstrated that the presented method can provide high-graded images at a shorter time cost. Furthermore, the stability of this method deserves investigation even under quite ill-posed conditions.

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Abbreviations

FMT:

Fluorescence molecular tomography

PR:

Permissible region

PCA:

Principal component analysis

SPECT:

Single-photon emission computed tomography

CLT:

Cerenkov luminescence tomography

PCCT:

Phase-contrast X-ray computed tomography

RTE:

Radiative transfer equation

DE:

Diffuse equation

FEM:

Finite element method

LE:

Location errors

nRMSE:

Normalized root-mean-square error

IVTCG:

Incomplete variables truncated conjugate gradient

CGLS:

Conjugate gradient least squares

References

  1. Deliolanis, N., Lasser, T., Hyde, D., Soubret, A., Ripoll, J., Ntziachristos, V.: Free-space fluorescence molecular tomography utilizing 360 degrees geometry projections. Opt. Lett. 32, 382–384 (2007)

    Article  ADS  Google Scholar 

  2. Cao, X., Wang, X., Zhang, B., Liu, F., Luo, J.W., Bai, J.: Accelerated image reconstruction in fluorescence molecular tomography using dimension reduction. Biomed. Opt. Express 4, 1–14 (2013)

    Article  Google Scholar 

  3. Razansky, D., Deliolanis, N.C., Vinegoni, C., Ntziachristos, V.: Deep tissue optical and optoacoustic molecular imaging technologies for pre-clinical research and drug discovery. Curr. Pharm. Biotechnol. 13, 504–522 (2012)

    Article  Google Scholar 

  4. Dimarzio, C.A., Niedre, M.: Pre-clinical optical molecular imaging in the lung: technological challenges and future prospects. J. Thorac. Dis. 4, 556–557 (2012)

    Google Scholar 

  5. Song, X.L., Wang, D.F., Chen, N.G., Bai, J., Wang, H.: Reconstruction for free-space fluorescence tomography using a novel hybrid adaptive finite element algorithm. Opt. Express 26, 18300–18317 (2007)

    Article  ADS  Google Scholar 

  6. Ntziachristos, V.: Going deeper than microscopy: the optical imaging frontier in biology. Nat. Methods 8, 603–614 (2010)

    Article  Google Scholar 

  7. Guven, M., Reilly-Raska, L., Zhou, L., Yazici, B.: Discretization error analysis and adaptive meshing algorithms for fluorescence diffuse optical tomography—part I. IEEE. Trans. Med. Imaging 2, 217–229 (2010)

    Article  Google Scholar 

  8. Zhang, J.L., Shi, J.W., Zuo, S.M., Liu, F., Luo, J.W., Bai, J.: Fast reconstruction in fluorescence molecular tomography using data compression of intra- and inter-projections. Chin. Opt. Lett. 13, 52–56 (2015)

    Google Scholar 

  9. Zhang, J.L., Shi, J.W., Cao, X., Liu, F., Luo, J.W., Bai, J.: Fast reconstruction of fluorescence molecular tomography via a permissible region extraction strategy. J. Opt. Soc. Am. A 31, 1886–1894 (2014)

    Article  ADS  Google Scholar 

  10. Hu, Z.H., Chen, X.L., Liang, J.M., Qu, X.C., Chen, D.F., Yang, W.D., Wang, J., Cao, F., Tian, J.: Single photon emission computed tomography-guided Cerenkov luminescence tomography. J. Appl. Phys. 112, 024703 (2012)

    Article  ADS  Google Scholar 

  11. Cao, X., Zhang, B., Wang, X., Liu, F., Liu, K., Luo, J.W., Bai, J.: An adaptive Tikhonov regularization method for fluorescence molecular tomography. Med. Biol. Eng. Comput. 51, 849–858 (2013)

    Article  Google Scholar 

  12. Xie, W.H., Deng, Y., Wang, K., Yang, X.Q., Luo, Q.M.: Reweighted L1 regularization for restraining artifacts in FMT reconstruction images with limited measurements. Opt. Lett. 39, 4148–4151 (2014)

    Article  ADS  Google Scholar 

  13. He, X.W., Liang, J.M., Wang, X.R., Yu, J.J., Qu, X.C., Wang, X.D., Hou, Y.B., Chen, D.F., Liu, F., Tian, J.: Sparse reconstruction for quantitative bioluminescence tomography based on the incomplete variables truncated conjugate gradient method. Opt. Express 18, 24825–24841 (2010)

    Article  ADS  Google Scholar 

  14. Yi, H.J., Wei, H.N., Peng, J.Y., Hou, Y.Q., He, X.W.: Adaptive threshold method for recovered images of FMT. J. Opt. Soc. Am. A 35, 256–261 (2018)

    Article  ADS  Google Scholar 

  15. Mohajerani, P., Hipp, A., Willner, M., Marschner, M., Arsic, M.T., Ma, X.P., Burton, N.C., Klemm, U., Radrich, K., Ermolayev, V., Tzoumas, S., Siveke, J.T., Bech, M., Pfeiffer, F., Ntziachristos, V.: FMT-PCCT: hybrid fluorescence molecular tomography—X-ray phase-contrast CT imaging of mouse models. IEEE Trans. Med. Imaging 33, 1434–1446 (2014)

    Article  Google Scholar 

  16. 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, 323–345 (2005)

    Article  ADS  Google Scholar 

  17. Bai, J., Xu, Z.: Fluorescence molecular tomography[M]. Mol. Imaging 185–216 (2013)

  18. 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, 8630–8646 (2010)

    Article  ADS  Google Scholar 

  19. Zhang, X.X., Zhang, J.L., Luo, J.W.: Reconstruction of in vivo fluorophore concentration variation with structural priors and smooth penalty. Appl. Opt. 55, 2732–2740 (2016)

    Article  ADS  Google Scholar 

  20. Yi, H.J., Chen, D.F., Qu, X.C., Peng, K., Chen, X.L., Zhou, Y.Y., Tian, J., Liang, J.M.: Multilevel, hybrid regularization method for reconstruction of fluorescent molecular tomography. Appl. Opt. 51, 975–986 (2012)

    Article  ADS  Google Scholar 

  21. Wang, B., Zhang, X., Hou, Y.Q., He, X.L., Yi, H.J., He, X.L.: Efficient image reconstruction for fluorescence molecular tomography via linear regression approximation scheme with dual augmented Lagrangian method. Multimed. Syst. 25, 135–145 (2019)

    Article  Google Scholar 

  22. Yi, H.J., Zhang, X., Peng, J.Y., Zhao, F.J., Wang, X.D., Hou, Y.Q., Chen, D.F., He, X.W.: Reconstruction for limited-projection fluorescence molecular tomography based on a double-mesh strategy. Biomed. Res. Int. 2016, 1–11 (2016)

    Google Scholar 

  23. Oh, S., Kwon, S., Yun, J.H.: Image restoration by the global conjugate gradient least squares method. J. Appl. Math. Inform. 31, 353–363 (2013)

    Article  MathSciNet  Google Scholar 

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Acknowledgements

This work was supported by the National Natural Science Foundation of China under Grant (Nos. 11571012, 2016JM6025); China Postdoctoral Science Foundation under Grant (Nos. 2016M602851); Shaanxi Provincial Education Department under Grant (Nos. 2018JQ6099); Industrialization Project of Shaanxi Education Department under Grant (Nos. 16JF026, 17JF027).

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Correspondence to Huangjian Yi or Xiaowei He.

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Jiao, P., Yi, H., Hu, Y. et al. A permissible region strategy for fluorescence molecular tomography. Opt Rev 26, 523–530 (2019). https://doi.org/10.1007/s10043-019-00520-8

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