Limited view cone-beam x-ray luminescence tomography based on depth compensation and group sparsity prior

Abstract. Significance: As a promising hybrid imaging technique with x-ray excitable nanophosphors, cone-beam x-ray luminescence computed tomography (CB-XLCT) has been proposed for in-depth biological imaging applications. In situations in which the full rotation of the imaging object (or x-ray source) is inapplicable, the x-ray excitation is limited by geometry, or a lower x-ray excitation dose is mandatory, limited view CB-XLCT reconstruction would be essential. However, this will result in severe ill-posedness and poor image quality. Aim: The aim is to develop a limited view CB-XLCT imaging strategy to reduce the scanning span and a corresponding reconstruction method to achieve robust imaging performance. Approach: In this study, a group sparsity-based reconstruction method is proposed with the consideration that nanophosphors usually cluster in certain regions, such as tumors or major organs such as the liver. In addition, depth compensation (DC) is adopted to avoid the depth inconsistency caused by a limited view strategy. Results: Experiments using numerical simulations and physical phantoms with different edge-to-edge distances were carried out to illustrate the validity of the proposed method. The reconstruction results showed that the proposed method outperforms conventional methods in terms of localization accuracy, target shape, image contrast, and spatial resolution with two perpendicular projections. Conclusions: A limited view CB-XLCT imaging strategy with two perpendicular projections and a reconstruction method based on DC and group sparsity, which is essential for fast CB-XLCT imaging and for some practical imaging applications, such as imaging-guided surgery, is proposed.

[1]  Jie Tian,et al.  Bioluminescence Tomography Based on Gaussian Weighted Laplace Prior Regularization for In Vivo Morphological Imaging of Glioma , 2017, IEEE Transactions on Medical Imaging.

[2]  Xiaohui Xie,et al.  Split Bregman method for large scale fused Lasso , 2010, Comput. Stat. Data Anal..

[3]  Junyan Rong,et al.  Spectral-resolved cone-beam X-ray luminescence computed tomography with principle component analysis. , 2018, Biomedical optics express.

[4]  L Xing,et al.  Limited-angle x-ray luminescence tomography: methodology and feasibility study , 2011, Physics in medicine and biology.

[5]  Yi Sun,et al.  A permissible region extraction based on a knowledge priori for X-ray luminescence computed tomography , 2017, Multimedia Systems.

[6]  Hongbing Lu,et al.  A wavelet-based single-view reconstruction approach for cone beam x-ray luminescence tomography imaging. , 2014, Biomedical optics express.

[7]  Jianwen Luo,et al.  Weighted depth compensation algorithm for fluorescence molecular tomography reconstruction. , 2012, Applied optics.

[8]  Qimei Liao,et al.  Fast X-Ray Luminescence Computed Tomography Imaging , 2014, IEEE Transactions on Biomedical Engineering.

[9]  Jie Tian,et al.  Cone beam x-ray luminescence computed tomography: a feasibility study. , 2013, Medical physics.

[10]  Simon R Cherry,et al.  Numerical simulation of x-ray luminescence optical tomography for small-animal imaging , 2014, Journal of biomedical optics.

[11]  J J Vaquero,et al.  Fluorescence diffuse optical tomography using the split Bregman method. , 2011, Medical physics.

[12]  Lei Xing,et al.  X-Ray Luminescence Computed Tomography via Selective Excitation: A Feasibility Study , 2010, IEEE Transactions on Medical Imaging.

[13]  Lei Xing,et al.  Tomographic molecular imaging of x-ray-excitable nanoparticles. , 2010, Optics letters.

[14]  Junyan Rong,et al.  Regularized reconstruction based on joint L1 and total variation for sparse-view cone-beam X-ray luminescence computed tomography. , 2018, Biomedical optics express.

[15]  Fei Liu,et al.  Reconstruction for limited-projection fluorescence molecular tomography based on projected restarted conjugate gradient normal residual. , 2011, Optics letters.

[16]  Jie Tian,et al.  Reconstruction of Fluorescence Molecular Tomography via a Fused LASSO Method Based on Group Sparsity Prior , 2019, IEEE Transactions on Biomedical Engineering.

[17]  L Xing,et al.  Hybrid x-ray/optical luminescence imaging: characterization of experimental conditions. , 2010, Medical physics.

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

[19]  Jianwen Luo,et al.  Separating structures of different fluorophore concentrations by principal component analysis on multispectral excitation-resolved fluorescence tomography images. , 2013, Biomedical optics express.

[20]  Junyan Rong,et al.  Sparse view cone beam X-ray luminescence tomography based on truncated singular value decomposition. , 2018, Optics express.

[21]  Jacek Gondzio,et al.  A Preconditioner for A Primal-Dual Newton Conjugate Gradient Method for Compressed Sensing Problems , 2014, SIAM J. Sci. Comput..

[22]  Peng Gao,et al.  Direct prior regularization from anatomical images for cone beam x-ray luminescence computed tomography reconstruction , 2018, Medical Imaging.

[23]  Hanli Liu,et al.  Depth-compensated diffuse optical tomography enhanced by general linear model analysis and an anatomical atlas of human head , 2014, NeuroImage.

[24]  Qimei Liao,et al.  In vivo x-ray luminescence tomographic imaging with single-view data. , 2013, Optics letters.

[25]  Xin Wang,et al.  An adaptive Tikhonov regularization method for fluorescence molecular tomography , 2013, Medical & Biological Engineering & Computing.

[26]  Marc Teboulle,et al.  A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems , 2009, SIAM J. Imaging Sci..

[27]  Wei Zhang,et al.  Sensitivity study of x-ray luminescence computed tomography. , 2017, Applied optics.

[28]  Junyan Rong,et al.  Resolving adjacent nanophosphors of different concentrations by excitation-based cone-beam X-ray luminescence tomography. , 2017, Biomedical optics express.

[29]  Ying Liu,et al.  Single-view cone-beam x-ray luminescence optical tomography based on Group_YALL1 method , 2019, Physics in medicine and biology.