简化球谐近似与拉普拉斯正则化的FMT成像方法

doi:10.3969/j.issn.1001-2400.2015.01.013

Abstract

Abstract:

As an emerging optical molecular imaging technology, fluorescence molecular tomography can efficiently reconstruct concentrations and three dimensional distributions of the buried fluorophore in small animals and diagnose the early cancer. For the purpose of improving the performance of the reconstructed image, simplified spherical harmonics approximation (SP_N) based on the radiative transport equation (RTE)is proposed to perform the forward simulation. To overcome the influence of ill-posedness and receive a more accurate reconstructed image, the Laplace regularization method is introduced to reconstruct the inverse problem. Numerical experiments reveal that the proposed method can acquire high-quality reconstructed images, especially of the small object and multi-objects.

Key words: fluorescence imaging, tomography imaging, simplified spherical harmonics approximation, regularization

LI Wei;YI Huangjian;ZHANG Qitan;LIANG Jimin. Fluorescence molecular tomography method using simplified spherical harmonics approximation and Laplace regularization[J].J4, 2015, 42(1): 82-85.

References

［1］ Massoud T F, Gambhir S S. Molecular Imaging in Living Subjects: Seeing Fundamental Biological Processes in a New Light ［J］. Genes ＆ Development, 2003, 17(5): 545-580.
［2］ Ntziachristos V, Ripoll J, Wang L V, et al. Looking and Listening to Light: the Evolution of Whole Body Photonic Imaging ［J］. Nature Biotechnology, 2005, 23(3): 313-320.
［3］ Ale A, Ermolayev V, Herzog E, et al. FMT-XCT: in Vivo Animal Studies with Hybrid Fluorescence Molecular Tomography-X-Ray Computed Tomography ［J］. Nature methods, 2012, 9(6): 615-620.
［4］ Stelter L, Evans M J, Jungbluth A A, et al. Imaging of Tumor Vascularization Using Fluorescence Molecular Tomography yo Monitor Arginine Deiminase Treatment In Melanoma［J］. Molecular Imaging, 2013, 12(1): 67-73.
［5］ Deliolanis N C, Ntziachristos V. Fluorescence Molecular Tomography of Brain Tumors in Mice ［J］. Cold Spring Harbor Protocols, 2013, 2013(5): 074245.
［6］ Ale A, Schulz R B, Sarantopoulos A, et al. Imaging performance of a Hybrid X-Ray Computed Tomography-Fluorescence Molecular Tomography System Using Priors ［J］. Medical Physics, 2010, 37(5): 1976-1986.
［7］ Klose A D, Ntziachristos V, Hielscher A. The Inverse Source Problem Based on the Radiative Transfer Equation in Optical Molecular Imaging ［J］. Journal of Computational Physics, 2005, 202(1): 323-345.
［8］ Ducros N, Bassi A, Valentini G, et al. Fluorescence Molecular Tomography of an Animal Model Using Structured Light Rotating View Acquisition ［J］. Journal of Biomedical Optics, 2013, 18(2): 020503.
［9］ Klose A D, Larsen E W. Light Transport In Biological Tissue Based on the Simplified Spherical Harmonics Equations ［J］. Journal of Computational Physics, 2006, 220(1): 441-470.
［10］ Han D, Tian J, Liu K, et al. Sparsity Promoting Tomographic Fluorescence Imaging with Simplified Spherical Harmonics Approximation ［J］. IEEE Transactions on Biomedical Engineering, 2010, 57(10): 2564-2567.
［11］ Jermyn M, Ghadyani H, Mastanduno M A, et al. Fast Segmentation and High-quality Three-dimensional Volume Mesh Creation from Medical Images for Diffuse Optical Tomography ［J］. Journal of Biomedical Optics, 2013, 18(8): 086007.
［12］ Davis S C, Dehghani H, Wang J, et al. Image-guided Diffuse Optical Fluorescence Tomography Implemented with Laplacian-type Regularization ［J］. Optics Express, 2007, 15(7): 4066-4082.
［13］ Dehghani H, Eames M E, Yalavarthy P K, et al. Near Infrared Optical Tomography Using Nirfast: Algorithm for Numerical Model and Image Reconstruction ［J］. Communications in Numerical Methods in Engineering, 2009, 25(6): 711-732.

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Fluorescence molecular tomography method using simplified spherical harmonics approximation and Laplace regularization

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