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Shi J, Zhang B, Liu F, Luo J, Bai J. Efficient L1 regularization-based reconstruction for fluorescent molecular tomography using restarted nonlinear conjugate gradient. OPTICS LETTERS 2013; 38:3696-9. [PMID: 24104850 DOI: 10.1364/ol.38.003696] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
For the ill-posed fluorescent molecular tomography (FMT) inverse problem, the L1 regularization can protect the high-frequency information like edges while effectively reduce the image noise. However, the state-of-the-art L1 regularization-based algorithms for FMT reconstruction are expensive in memory, especially for large-scale problems. An efficient L1 regularization-based reconstruction algorithm based on nonlinear conjugate gradient with restarted strategy is proposed to increase the computational speed with low memory consumption. The reconstruction results from phantom experiments demonstrate that the proposed algorithm can obtain high spatial resolution and high signal-to-noise ratio, as well as high localization accuracy for fluorescence targets.
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Yu J, He X, Geng G, Liu F, Jiao LC. Hybrid multilevel sparse reconstruction for a whole domain bioluminescence tomography using adaptive finite element. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2013; 2013:548491. [PMID: 23533542 PMCID: PMC3603587 DOI: 10.1155/2013/548491] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/15/2012] [Accepted: 01/26/2013] [Indexed: 11/18/2022]
Abstract
Quantitative reconstruction of bioluminescent sources from boundary measurements is a challenging ill-posed inverse problem owing to the high degree of absorption and scattering of light through tissue. We present a hybrid multilevel reconstruction scheme by combining the ability of sparse regularization with the advantage of adaptive finite element method. In view of the characteristics of different discretization levels, two different inversion algorithms are employed on the initial coarse mesh and the succeeding ones to strike a balance between stability and efficiency. Numerical experiment results with a digital mouse model demonstrate that the proposed scheme can accurately localize and quantify source distribution while maintaining reconstruction stability and computational economy. The effectiveness of this hybrid reconstruction scheme is further confirmed with in vivo experiments.
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Affiliation(s)
- Jingjing Yu
- School of Physics and Information Technology, Shaanxi Normal University, Xi'an, Shanxi 710062, China
| | - Xiaowei He
- School of Information Sciences and Technology, Northwest University, Xi'an, Shanxi 710069, China
| | - Guohua Geng
- School of Information Sciences and Technology, Northwest University, Xi'an, Shanxi 710069, China
| | - Fang Liu
- School of Computer Science and Technology, Xidian University, Xi'an, Shanxi 710071, China
- Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xi'an, Shanxi 710071, China
| | - L. C. Jiao
- Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xi'an, Shanxi 710071, China
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ZHOU T, ANDO T, LIAO H, KOBAYASHI E, SAKUMA I. Piecewise Weighted Tikhonov Regularization for Reconstructing Fluorophore Distribution in Tissue using Mesoscopic Epifluorescence Tomography. ADVANCED BIOMEDICAL ENGINEERING 2013. [DOI: 10.14326/abe.2.84] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Affiliation(s)
- Tuo ZHOU
- Graduate School of Engineering, The University of Tokyo
| | - Takehiro ANDO
- Graduate School of Engineering, The University of Tokyo
| | - Hongen LIAO
- Graduate School of Engineering, The University of Tokyo
| | | | - Ichiro SAKUMA
- Graduate School of Engineering, The University of Tokyo
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Zhang Q, Chen X, Qu X, Liang J, Tian J. Comparative studies of l(p)-regularization-based reconstruction algorithms for bioluminescence tomography. BIOMEDICAL OPTICS EXPRESS 2012; 3:2916-36. [PMID: 23162729 PMCID: PMC3493215 DOI: 10.1364/boe.3.002916] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2012] [Revised: 10/18/2012] [Accepted: 10/19/2012] [Indexed: 05/16/2023]
Abstract
Inverse source reconstruction is the most challenging aspect of bioluminescence tomography (BLT) because of its ill-posedness. Although many efforts have been devoted to this problem, so far, there is no generally accepted method. Due to the ill-posedness property of the BLT inverse problem, the regularization method plays an important role in the inverse reconstruction. In this paper, six reconstruction algorithms based on l(p) regularization are surveyed. The effects of the permissible source region, measurement noise, optical properties, tissue specificity and source locations on the performance of the reconstruction algorithms are investigated using a series of single source experiments. In order to further inspect the performance of the reconstruction algorithms, we present the double sources and the in vivo mouse experiments to study their resolution ability and potential for a practical heterogeneous mouse experiment. It is hoped to provide useful guidance on algorithm development and application in the related fields.
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Affiliation(s)
- Qitan Zhang
- School of Life Sciences and Technology, Xidian University,
Xi’an, Shaanxi 710071, China
- Contributed equally to this work
| | - Xueli Chen
- School of Life Sciences and Technology, Xidian University,
Xi’an, Shaanxi 710071, China
- Contributed equally to this work
| | - Xiaochao Qu
- School of Life Sciences and Technology, Xidian University,
Xi’an, Shaanxi 710071, China
| | - Jimin Liang
- School of Life Sciences and Technology, Xidian University,
Xi’an, Shaanxi 710071, China
| | - Jie Tian
- School of Life Sciences and Technology, Xidian University,
Xi’an, Shaanxi 710071, China
- Institute of Automation, Chinese Academy of Sciences, Beijing
100190, China
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Basevi HRA, Tichauer KM, Leblond F, Dehghani H, Guggenheim JA, Holt RW, Styles IB. Compressive sensing based reconstruction in bioluminescence tomography improves image resolution and robustness to noise. BIOMEDICAL OPTICS EXPRESS 2012; 3:2131-41. [PMID: 23024907 PMCID: PMC3447555 DOI: 10.1364/boe.3.002131] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2012] [Revised: 06/27/2012] [Accepted: 07/04/2012] [Indexed: 05/08/2023]
Abstract
Bioluminescence Tomography attempts to quantify 3-dimensional luminophore distributions from surface measurements of the light distribution. The reconstruction problem is typically severely under-determined due to the number and location of measurements, but in certain cases the molecules or cells of interest form localised clusters, resulting in a distribution of luminophores that is spatially sparse. A Conjugate Gradient-based reconstruction algorithm using Compressive Sensing was designed to take advantage of this sparsity, using a multistage sparsity reduction approach to remove the need to choose sparsity weighting a priori. Numerical simulations were used to examine the effect of noise on reconstruction accuracy. Tomographic bioluminescence measurements of a Caliper XPM-2 Phantom Mouse were acquired and reconstructions from simulation and this experimental data show that Compressive Sensing-based reconstruction is superior to standard reconstruction techniques, particularly in the presence of noise.
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Affiliation(s)
- Hector R. A. Basevi
- PSIBS, University of Birmingham, Edgbaston, Birmingham, B15 2TT,
UK
- School of Computer Science, University of Birmingham, Edgbaston, Birmingham, B15 2TT,
UK
| | - Kenneth M. Tichauer
- Thayer School of Engineering, Dartmouth College, 8000 Cummings Hall, Hanover, New Hampshire 03755,
USA
| | - Frederic Leblond
- Thayer School of Engineering, Dartmouth College, 8000 Cummings Hall, Hanover, New Hampshire 03755,
USA
| | - Hamid Dehghani
- PSIBS, University of Birmingham, Edgbaston, Birmingham, B15 2TT,
UK
- School of Computer Science, University of Birmingham, Edgbaston, Birmingham, B15 2TT,
UK
- Thayer School of Engineering, Dartmouth College, 8000 Cummings Hall, Hanover, New Hampshire 03755,
USA
| | - James A. Guggenheim
- PSIBS, University of Birmingham, Edgbaston, Birmingham, B15 2TT,
UK
- School of Computer Science, University of Birmingham, Edgbaston, Birmingham, B15 2TT,
UK
| | - Robert W. Holt
- Department of Physics & Astronomy, Dartmouth College, Hanover, New Hampshire 03755,
USA
| | - Iain B. Styles
- School of Computer Science, University of Birmingham, Edgbaston, Birmingham, B15 2TT,
UK
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He X, Liang J, Wang X, Yu J, Qu X, Wang X, Hou Y, Chen D, Liu F, Tian J. Sparse reconstruction for quantitative bioluminescence tomography based on the incomplete variables truncated conjugate gradient method. OPTICS EXPRESS 2010; 18:24825-41. [PMID: 21164828 DOI: 10.1364/oe.18.024825] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
In this paper, we present an incomplete variables truncated conjugate gradient (IVTCG) method for bioluminescence tomography (BLT). Considering the sparse characteristic of the light source and insufficient surface measurement in the BLT scenarios, we combine a sparseness-inducing (ℓ1 norm) regularization term with a quadratic error term in the IVTCG-based framework for solving the inverse problem. By limiting the number of variables updated at each iterative and combining a variable splitting strategy to find the search direction more efficiently, it obtains fast and stable source reconstruction, even without a priori information of the permissible source region and multispectral measurements. Numerical experiments on a mouse atlas validate the effectiveness of the method. In vivo mouse experimental results further indicate its potential for a practical BLT system.
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Affiliation(s)
- Xiaowei He
- Life Sciences Research Center, School of Life Sciences and Technology, Xidian University, Xi’an 710071, China
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