Source sparsity based primal-dual interior-point method for three-dimensional bioluminescence tomography

Yang

et al. 2012

J. Biomed. Opt.

Self Cite

Abstract. Bioluminescence tomography (BLT) has been successfully applied to the detection and therapeutic evaluation of solid cancers. However, the existing BLT reconstruction algorithms are not accurate enough for cavity cancer detection because of neglecting the void problem. Motivated by the ability of the hybrid radiosity-diffusion model (HRDM) in describing the light propagation in cavity organs, an HRDM-based BLT reconstruction algorithm was provided for the specific problem of cavity cancer detection. HRDM has been applied to optical tomography but is limited to simple and regular geometries because of the complexity in coupling the boundary between the scattering and void region. In the provided algorithm, HRDM was first applied to three-dimensional complicated and irregular geometries and then employed as the forward light transport model to describe the bioluminescent light propagation in tissues. Combining HRDM with the sparse reconstruction strategy, the cavity cancer cells labeled with bioluminescent probes can be more accurately reconstructed. Compared with the diffusion equation based reconstruction algorithm, the essentiality and superiority of the HRDM-based algorithm were demonstrated with simulation, phantom and animal studies. An in vivo gastric cancer-bearing nude mouse experiment was conducted, whose results revealed the ability and feasibility of the HRDM-based algorithm in the biomedical application of gastric cancer detection.

“…Equation (9) can be efficiently solved using a common optimization method, such as the primal-dual interior-point algorithm utilized in this paper. 24 …”

Section: Inverse Reconstruction: Finite Element Discretization and Spmentioning

confidence: 99%

mentioning

confidence: 99%

Comparisons of hybrid radiosity-diffusion model and diffusion equation for bioluminescence tomography in cavity cancer detection

Yang

et al. 2012

J. Biomed. Opt.

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“…To evaluate the performance of our home-developed tri-modality BLT/FMT/micro-CT system, we have developed some reconstruction algorithms for 3D optical imaging based on the diffusion equation (DE) and the finite element method (FEM), including the adaptive hp FEM (hp-FEM) 13 , Tikhonov regularization based truncated total least squares and multi-phase level set algorithm [14][15][16] , sparse regularization based truncated Newton interior-point method and incomplete variables truncated conjugate gradient method [17][18][19] . Furthermore, in order to deal with the problem of early gastric cancer detection, we proposed a hybrid diffusion-radiosity theory (HDRT) model based reconstruction algorithm 24 and an endoscopic algorithm 25 .…”

Section: Development Of the Reconstruction Algorithmsmentioning

confidence: 99%

“…CLT is an emerging molecular imaging technology based on the well-known phenomenon of Cerenkov radiation 8 . Secondly, based on the home-developed tri-modality BLT/FMT/micro-CT system and the requirements of biomedical applications, we proposed several reconstruction algorithms for 3D optical imaging which have been well validated using the numerical simulations and small animal experiments [9][10][11][12][13][14][15][16][17][18][19][20] . In addition, based on the Monte Carlo method and free space light transport theory, we developed a simulation platform for optical imaging named molecular optical simulation environment (MOSE), which provides an accurate solution to light transport both in biological tissues and in free space 21,22 .…”

Section: Introductionmentioning

confidence: 99%

Multi-modality molecular imaging for gastric cancer research

Liang

Optical Sensors and Biophotonics III

Liu

et al. 2011

Self Cite

Because of the ability of integrating the strengths of different modalities and providing fully integrated information, multi-modality molecular imaging techniques provide an excellent solution to detecting and diagnosing earlier cancer, which remains difficult to achieve by using the existing techniques. In this paper, we present an overview of our research efforts on the development of the optical imaging-centric multi-modality molecular imaging platform, including the development of the imaging system, reconstruction algorithms and preclinical biomedical applications. Primary biomedical results show that the developed optical imaging-centric multi-modality molecular imaging platform may provide great potential in the preclinical biomedical applications and future clinical translation.

“…Equation (12) is the final formula and can be efficiently solved using a common optimization method, such as the primal-dual interior-point algorithm. 10 …”

Section: Introductionmentioning

confidence: 99%

Feasibility study of endoscopic x-ray luminescence computed tomography: Simulation demonstration and phantom application

Journal of Applied Physics

Liang

Cao

et al. 2013

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Even though endoscopic fluorescence diffuse optical tomography (eFDOT) exhibits significant potential, currently its application is limited due to the existence of strong autofluorescence and the imaging inaccuracy caused by a very short source-detector distance. Motivated by the emerging X-ray luminescence computed tomography (XLCT) technology, we presented an endoscopic XLCT (eXLCT) methodology. In the methodology, the aperture angle of the objective was incorporated into the forward model, providing a more accurate description of light propagation. Numerical simulation with a heterogeneous geometry and an imaging experiment with a physical phantom were illustrated to demonstrate the feasibility of the presented eXLCT methodology.