Reconstruction of localized fluorescent target from multi-view continuous-wave surface images of small animal with lp sparsity regularization.

Fluorescence diffuse optical tomography using a multi-view continuous-wave and non-contact measurement system and an algorithm incorporating the lp (0 < p ≤ 1) sparsity regularization reconstructs a localized fluorescent target in a small animal. The measurement system provides a total of 25 fluorescence surface 2D-images of an object, which are acquired by a CCD camera from five different angles of view with excitation from five different angles. Fluorescence surface emissions from five different angles of view are simultaneously imaged on the CCD sensor, thus leading to fast acquisition of the 25 images within three minutes. The distributions of the fluorophore are reconstructed by solving the inverse problem based on the photon diffusion equations. In the reconstruction process incorporating the lp sparsity regularization, the regularization term is reformulated as a differentiable function for gradient-based non-linear optimization. Numerical simulations and phantom experiments show that the use of the lp sparsity regularization improves the localization of the target and quantitativeness of the fluorophore concentration. A mouse experiment demonstrates that a localized fluorescent target in a mouse is successfully reconstructed.

[1]  A. Liebert,et al.  Neurotoxic effects of indocyanine green -cerebellar granule cell culture viability study. , 2014, Biomedical optics express.

[2]  Masa-aki Sato,et al.  Hierarchical Bayesian estimation improves depth accuracy and spatial resolution of diffuse optical tomography. , 2012, Optics express.

[3]  Fenghua Tian,et al.  Sparsity enhanced spatial resolution and depth localization in diffuse optical tomography , 2012, Biomedical optics express.

[4]  R. Leahy,et al.  Joint L1 and total variation regularization for fluorescence molecular tomography , 2012, Physics in medicine and biology.

[5]  Xiaochao Qu,et al.  Multilevel, hybrid regularization method for reconstruction of fluorescent molecular tomography. , 2012, Applied optics.

[6]  Yukio Yamada,et al.  Improvement of image quality of time-domain diffuse optical tomography with lp sparsity regularization , 2011, Biomedical optics express.

[7]  Jie Tian,et al.  Efficient reconstruction method for L1 regularization in fluorescence molecular tomography. , 2010, Applied optics.

[8]  C. Clason,et al.  Total variation regularization for nonlinear fluorescence tomography with an augmented Lagrangian splitting approach. , 2010, Applied optics.

[9]  Yukio Yamada,et al.  Reconstruction of fluorescence/bioluminescence sources in biological medium with spatial filter. , 2010, Optics express.

[10]  Jie Tian,et al.  A fast reconstruction algorithm for fluorescence molecular tomography with sparsity regularization. , 2010, Optics express.

[11]  T. Chan,et al.  Source reconstruction for spectrally-resolved bioluminescence tomography with sparse a priori information. , 2009, Optics express.

[12]  Martin Schweiger,et al.  Information theoretic regularization in diffuse optical tomography. , 2009, Journal of the Optical Society of America. A, Optics, image science, and vision.

[13]  Zhaoshui He,et al.  Improved FOCUSS Method With Conjugate Gradient Iterations , 2009, IEEE Transactions on Signal Processing.

[14]  D Calvetti,et al.  An adaptive smoothness regularization algorithm for optical tomography. , 2008, Optics express.

[15]  Feng Gao,et al.  Total light approach of time-domain fluorescence diffuse optical tomography. , 2008, Optics express.

[16]  R. Perutz.  A Catalytic Foothold for Fluorocarbon Reactions , 2008, Science.

[17]  Mark A Neifeld,et al.  Sparsity constrained regularization for multiframe image restoration. , 2008, Journal of the Optical Society of America. A, Optics, image science, and vision.

[18]  Arye Nehorai,et al.  Image reconstruction for diffuse optical tomography using sparsity regularization and expectation-maximization algorithm. , 2007, Optics express.

[19]  Hamid Dehghani,et al.  Structural information within regularization matrices improves near infrared diffuse optical tomography. , 2007, Optics express.

[20]  A. Adibi,et al.  Optimal sparse solution for fluorescent diffuse optical tomography: theory and phantom experimental results. , 2007, Applied optics.

[21]  Dezhong Yao,et al.  Lp Norm Iterative Sparse Solution for EEG Source Localization , 2007, IEEE Transactions on Biomedical Engineering.

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

[23]  M. Schweiger,et al.  Anisotropic diffusion regularization methods for diffuse optical tomography using edge prior information , 2006 .

[24]  R. Weissleder.  Molecular Imaging in Cancer , 2006, Science.

[25]  Simon R. Arridge,et al.  Three-dimensional whole-head optical tomography of passive motor evoked responses in the neonate , 2006, NeuroImage.

[26]  E. Miller,et al.  Quantitative spectroscopic diffuse optical tomography of the breast guided by imperfect a priori structural information , 2005, Physics in medicine and biology.

[27]  Nick Everdell,et al.  Optical tomography of the breast using a multi-channel time-resolved imager , 2005, Physics in medicine and biology.

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

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

[30]  Simon R. Arridge,et al.  Application of the finite-element method for the forward and inverse models in optical tomography , 1993, Journal of Mathematical Imaging and Vision.

[31]  A. Joshi,et al.  Adaptive finite element based tomography for fluorescence optical imaging in tissue. , 2004, Optics express.

[32]  Quing Zhu,et al.  Dual-mesh optical tomography reconstruction method with a depth correction that uses a priori ultrasound information. , 2004, Applied optics.

[33]  C. Bouman,et al.  Fluorescence optical diffusion tomography. , 2003, Applied optics.

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

[35]  S. Arridge,et al.  INSTITUTE OF PHYSICS PUBLISHING PHYSICS IN MEDICINE AND BIOLOGY , 2003 .

[36]  Brian Pogue,et al.  Quantitative fluorescence lifetime spectroscopy in turbid media: comparison of theoretical, experimental and computational methods. , 2002, Physics in medicine and biology.

[37]  R. Weissleder,et al.  Fluorescence molecular tomography resolves protease activity in vivo , 2002, Nature Medicine.

[38]  Wolfgang Ebert,et al.  Imaging of myocardial infarction: comparison of magnevist and gadophrin-3 in rabbits. , 2002, Journal of the American College of Cardiology.

[39]  Daniel J. Hawrysz,et al.  Developments toward diagnostic breast cancer imaging using near-infrared optical measurements and fluorescent contrast agents. , 2000, Neoplasia.

[40]  B. Pogue,et al.  Spatially variant regularization improves diffuse optical tomography. , 1999, Applied optics.

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

[42]  S Arridge,et al.  A gradient-based optimisation scheme foroptical tomography. , 1998, Optics express.

[43]  M S Patterson,et al.  Imaging of fluorescent yield and lifetime from multiply scattered light reemitted from random media. , 1997, Applied optics.

[44]  A. Welch,et al.  A review of the optical properties of biological tissues , 1990 .