Fast iterative image reconstruction methods for fully 3D multispectral bioluminescence tomography

Ahn, Sangtae; Chaudhari, Abhijit J.; Darvas, Felix; Bouman, Charles A.; Leahy, Richard M.

doi:10.1088/0031-9155/53/14/013

Cited by 76 publications

(54 citation statements)

References 66 publications

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“…[60]. Multispectral 3-D reconstruction has already been applied in microscopy [66]. Other 3-D acquisition and visualization techniques have already incorporated multispectral information [67]- [69].…”

Section: Multispectral Data Fusion For Depth Estimation Improvemenmentioning

confidence: 99%

Three-Dimensional Imaging With Multiple Degrees of Freedom Using Data Fusion

et al. 2015

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Section: Multispectral Data Fusion For Depth Estimation Improvemenmentioning

confidence: 99%

Three-Dimensional Imaging With Multiple Degrees of Freedom Using Data Fusion

et al. 2015

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“…One is a statistical method, e.g., a Monte Carlo [26,27] or Bayesian [28,29] method. The other is optimization using a least-squares criterion [18,19,30,31], a regularization method [18][19][20][21][22][23], a level set method [32,33], etc. As a new molecular modality, the methods used for CLT reconstruction are mainly focused on optimization.…”

Section: Introductionmentioning

confidence: 99%

“…The CLT model was solved iteratively using a preconditioned conjugate gradient method with Tikhonov regularization (TR) for bioluminescence tomography (BLT) [18,30]. Because this assumption is not necessarily true, Hu et al performed a heterogeneous CLT reconstruction [20], in which the adaptive hp-finite element method (hp-FEM) [34], originally designed for BLT, was employed for CLT reconstruction.…”

Section: Introductionmentioning

confidence: 99%

Probability method for Cerenkov luminescence tomography based on conformance error minimization

Ding¹,

Wang²,

Jie³

et al. 2014

Biomed. Opt. Express

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Cerenkov luminescence tomography (CLT) was developed to reconstruct a three-dimensional (3D) distribution of radioactive probes inside a living animal. Reconstruction methods are generally performed within a unique framework by searching for the optimum solution. However, the ill-posed aspect of the inverse problem usually results in the reconstruction being non-robust. In addition, the reconstructed result may not match reality since the difference between the highest and lowest uptakes of the resulting radiotracers may be considerably large, therefore the biological significance is lost. In this paper, based on the minimization of a conformance error, a probability method is proposed that consists of qualitative and quantitative modules. The proposed method first pinpoints the organ that contains the light source. Next, we developed a 0-1 linear optimization subject to a space constraint to model the CLT inverse problem, which was transformed into a forward problem by employing a region growing method to solve the optimization. After running through all of the elements used to grow the sources, a source sequence was obtained. Finally, the probability of each discrete node being the light source inside the organ was reconstructed. One numerical study and two in vivo experiments were conducted to verify the performance of the proposed algorithm, and comparisons were carried out using the hp-finite element method (hp-FEM). The results suggested that our proposed probability method was more robust and reasonable than hp-FEM.

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“…[19]. Multispectral 3D reconstruction has already been applied in microscopy [20]. Other 3D acquisition and visualization techniques have already incorporated multispectral information [21][22][23].…”

Section: Introductionmentioning

confidence: 99%

Multispectral integral imaging acquisition and processing using a monochrome camera and a liquid crystal tunable filter

Carmona¹,

Sánchez-Ortiga²,

Xiao³

et al. 2012

Opt. Express

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Abstract:This paper presents an acquisition system and a procedure to capture 3D scenes in different spectral bands. The acquisition system is formed by a monochrome camera, and a Liquid Crystal Tunable Filter (LCTF) that allows to acquire images at different spectral bands in the [480, 680]nm wavelength interval. The Synthetic Aperture Integral Imaging acquisition technique is used to obtain the elemental images for each wavelength. These elemental images are used to computationally obtain the reconstruction planes of the 3D scene at different depth planes. The 3D profile of the acquired scene is also obtained using a minimization of the variance of the contribution of the elemental images at each image pixel. Experimental results show the viability to recover the 3D multispectral information of the scene. Integration of 3D and multispectral information could have important benefits in different areas, including skin cancer detection, remote sensing and pattern recognition, among others.

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Fast iterative image reconstruction methods for fully 3D multispectral bioluminescence tomography

Cited by 76 publications

References 66 publications

Three-Dimensional Imaging With Multiple Degrees of Freedom Using Data Fusion

Three-Dimensional Imaging With Multiple Degrees of Freedom Using Data Fusion

Probability method for Cerenkov luminescence tomography based on conformance error minimization

Multispectral integral imaging acquisition and processing using a monochrome camera and a liquid crystal tunable filter

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