Three-dimensional bioluminescence tomography based on Bayesian approach.

Bioluminescence tomography (BLT) poses a typical ill-posed inverse problem with a large number of unknowns and a relatively limited number of boundary measurements. It is indispensable to incorporate a priori information into the inverse problem formulation in order to obtain viable solutions. In the paper, Bayesian approach has been firstly suggested to incorporate multiple types of a priori information for BLT reconstruction. Meanwhile, a generalized adaptive Gaussian Markov random field (GAGMRF) prior model for unknown source density estimation is developed to further reduce the ill-posedness of BLT on the basis of finite element analysis. Then the distribution of bioluminescent source can be acquired by maximizing the log posterior probability with respect to a noise parameter and the unknown source density. Furthermore, the use of finite element method makes the algorithm appropriate for complex heterogeneous phantom. The algorithm was validated by numerical simulation of a 3-D micro-CT mouse atlas and physical phantom experiment. The reconstructed results suggest that we are able to achieve high computational efficiency and accurate localization of bioluminescent source.

[1]  Jie Tian,et al.  A multilevel adaptive finite element algorithm for bioluminescence tomography. , 2006, Optics express.

[2]  E. Richer,et al.  Iterative reconstruction method for light emitting sources based on the diffusion equation. , 2005, Medical physics.

[3]  Jie Tian,et al.  Spectrally resolved bioluminescence tomography with adaptive finite element : methodology and simulation , 2007 .

[4]  Ge Wang,et al.  Iterative method for bioluminescence tomography based on the radiative transport equation , 2006, SPIE Optics + Photonics.

[5]  Jie Tian,et al.  Galerkin-based meshless methods for photon transport in the biological tissue. , 2008, Optics express.

[6]  Jie Tian,et al.  Fast cone-beam CT image reconstruction using GPU hardware , 2008 .

[7]  J. M. Martínez,et al.  A Box-Constrained Optimization Algorithm with Negative Curvature Directions and Spectral Projected Gradients , 2001 .

[8]  Jie Tian,et al.  An experimental cone-beam micro-CT system for small animal imaging , 2009, Medical Imaging.

[9]  Charles A. Bouman,et al.  Nonlinear multigrid algorithms for Bayesian optical diffusion tomography , 2001, IEEE Trans. Image Process..

[10]  R. Leahy,et al.  Hyperspectral and multispectral bioluminescence optical tomography for small animal imaging , 2005, Physics in medicine and biology.

[11]  Shan Zhao,et al.  Temperature-modulated bioluminescence tomography. , 2006, Optics express.

[12]  R. Henkelman,et al.  Combined magnetic resonance and bioluminescence imaging of live mice. , 2007, Journal of biomedical optics.

[13]  M. Jiang,et al.  Uniqueness theorems in bioluminescence tomography. , 2004, Medical physics.

[14]  Pamela C. Cosman,et al.  Dictionary design for text image compression with JBIG2 , 2001, IEEE Trans. Image Process..

[15]  Vasilis Ntziachristos,et al.  Noncontact optical imaging in mice with full angular coverage and automatic surface extraction. , 2007, Applied optics.

[16]  Hua-bei Jiang,et al.  Three-dimensional bioluminescence tomography with model-based reconstruction. , 2004, Optics express.

[17]  Ali Mohammad-Djafari,et al.  Joint estimation of parameters and hyperparameters in a Bayesian approach of solving inverse problems , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[18]  Vasilis Ntziachristos,et al.  A submillimeter resolution fluorescence molecular imaging system for small animal imaging. , 2003, Medical physics.

[19]  A. Chatziioannou,et al.  Tomographic bioluminescence imaging by use of a combined optical-PET (OPET) system: a computer simulation feasibility study , 2005, Physics in medicine and biology.

[20]  S. Gambhir,et al.  Molecular imaging in living subjects: seeing fundamental biological processes in a new light. , 2003, Genes & development.

[21]  Vasilis Ntziachristos,et al.  Looking and listening to light: the evolution of whole-body photonic imaging , 2005, Nature Biotechnology.

[22]  Dario Fasino,et al.  An inverse Robin problem for Laplace's equation: theoretical results and numerical methods , 1999 .

[23]  Kenneth M. Hanson,et al.  Model-based image reconstruction from time-resolved diffusion data , 1997, Medical Imaging.

[24]  Charles A. Bouman,et al.  Optical diffusion tomography by iterative- coordinate-descent optimization in a Bayesian framework , 1999 .

[25]  E. Hoffman,et al.  In vivo mouse studies with bioluminescence tomography. , 2006, Optics express.

[26]  Ken D. Sauer,et al.  A generalized Gaussian image model for edge-preserving MAP estimation , 1993, IEEE Trans. Image Process..

[27]  Jie Tian,et al.  Spectrally resolved bioluminescence tomography with adaptive finite element analysis: methodology and simulation , 2007, Physics in medicine and biology.

[28]  Jie Tian,et al.  An optimal permissible source region strategy for multispectral bioluminescence tomography. , 2008, Optics express.

[29]  B. Rice,et al.  In vivo imaging of light-emitting probes. , 2001, Journal of biomedical optics.

[30]  Peter P. Antich,et al.  Validating Bioluminescence Imaging as a High-Throughput, Quantitative Modality for Assessing Tumor Burden , 2004 .

[31]  S. Arridge.  Optical tomography in medical imaging , 1999 .

[32]  M. Schweiger,et al.  A finite element approach for modeling photon transport in tissue. , 1993, Medical physics.

[33]  Feng Gao,et al.  Experimental determination of optical properties in turbid medium by TCSPC technique , 2007, SPIE BiOS.

[34]  Jie Tian,et al.  Multimodality Molecular Imaging , 2008, IEEE Engineering in Medicine and Biology Magazine.

[35]  Geoffrey McLennan,et al.  Practical reconstruction method for bioluminescence tomography. , 2005, Optics express.

[36]  S R Arridge,et al.  Recent advances in diffuse optical imaging , 2005, Physics in medicine and biology.

[37]  Vasilis Ntziachristos,et al.  The inverse source problem based on the radiative transfer equation in optical molecular imaging , 2005 .

[38]  C. Contag,et al.  Advances in in vivo bioluminescence imaging of gene expression. , 2002, Annual review of biomedical engineering.

[39]  Ge Wang,et al.  A mouse optical simulation environment (MOSE) to investigate bioluminescent phenomena in the living mouse with the Monte Carlo method. , 2004, Academic radiology.

[40]  Vasilis Ntziachristos,et al.  Free-space fluorescence molecular tomography utilizing 360° geometry projections , 2007 .

[41]  Ming Jiang,et al.  Image reconstruction for bioluminescence tomography from partial measurement. , 2007, Optics express.

[42]  M. Schweiger,et al.  The finite element method for the propagation of light in scattering media: boundary and source conditions. , 1995, Medical physics.

[43]  José Mario Martínez,et al.  Large-Scale Active-Set Box-Constrained Optimization Method with Spectral Projected Gradients , 2002, Comput. Optim. Appl..

[44]  Hua-bei Jiang,et al.  Quantitative bioluminescence tomography guided by diffuse optical tomography. , 2008, Optics express.