Galerkin-based meshless methods for photon transport in the biological tissue

Qin, Chenghu; Tian, Jie; Yang, Xin; Li, Kai; Yan, Guorui; Feng, Jinchao; Lv, Yujie; Xu, Min

doi:10.1364/oe.16.020317

Cited by 33 publications

(22 citation statements)

References 29 publications

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“…Its computational efficiency is high and its applicability is wide. Numerical analysis methods include Finite Difference Method (FDM) [40], Boundary Element Method (BEM), Finite Element Method (FEM) [37,58] and Meshless Method (MM) method [59]. FDM uses equidistant grid points and regular grids to solve the forward problem, which is more efficient than irregular grids.…”

Section: Forward Problem Solvingmentioning

confidence: 99%

Recent methodology advances in fluorescence molecular tomography

Wang

Tian

2018

Vis. Comput. Ind. Biomed. Art

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Molecular imaging (MI) is a novel imaging discipline that has been continuously developed in recent years. It combines biochemistry, multimodal imaging, biomathematics, bioinformatics, cell & molecular physiology, biophysics, and pharmacology, and it provides a new technology platform for the early diagnosis and quantitative analysis of diseases, treatment monitoring and evaluation, and the development of comprehensive physiology. Fluorescence Molecular Tomography (FMT) is a type of optical imaging modality in MI that captures the three-dimensional distribution of fluorescence within a biological tissue generated by a specific molecule of fluorescent material within a biological tissue. Compared with other optical molecular imaging methods, FMT has the characteristics of high sensitivity, low cost, and safety and reliability. It has become the research frontier and research hotspot of optical molecular imaging technology. This paper took an overview of the recent methodology advances in FMT, mainly focused on the photon propagation model of FMT based on the radiative transfer equation (RTE), and the reconstruction problem solution consist of forward problem and inverse problem. We introduce the detailed technologies utilized in reconstruction of FMT. Finally, the challenges in FMT were discussed. This survey aims at summarizing current research hotspots in methodology of FMT, from which future research may benefit.

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Section: Forward Problem Solvingmentioning

confidence: 99%

Recent methodology advances in fluorescence molecular tomography

Wang

Tian

2018

Vis. Comput. Ind. Biomed. Art

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“…The radiative transport equation (RTE) is regarded as the standard method for light modeling, but its direct solution has a high computational cost. 21 To overcome the limitations of RTE, spherical harmonic expansion is employed. Based on the firstorder approximation of RTE, the telegraph equation (TE) is proposed for the calculation of the distribution of the excitation light 22 (1)…”

Section: Forward Model For Light Propagationmentioning

confidence: 99%

Self-guided reconstruction for time-domain fluorescence molecular lifetime tomography

Cai

Cheng

et al. 2016

J. Biomed. Opt

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Fluorescence probes have distinct yields and lifetimes when located in different environments, which makes the reconstruction of fluorescence molecular lifetime tomography (FMLT) challenging. To enhance the reconstruction performance of time-domain (TD) FMLT with heterogeneous targets, a self-guided L 1 regularization projected steepest descent (SGL1PSD) algorithm is proposed. Different from other algorithms performed in time domain, SGL1PSD introduces a time-resolved strategy into fluorescence yield reconstruction. The algorithm consists of four steps. Step 1 reconstructs the initial yield map with full time gate strategy; steps 2–4 reconstruct the inverse lifetime map, the yield map, and the inverse lifetime map again with time-resolved strategy, respectively. The reconstruction result of each step is used as a priori for the reconstruction of the next step. Projected iterated Tikhonov regularization algorithm is adopted for the yield map reconstructions in steps 1 and 3 to provide a solution with iterative refinement and nonnegative constraint. The inverse lifetime map reconstructions in steps 2 and 4 are based on L 1 regularization projected steepest descent algorithm, which employ the L 1 regularization to reduce the ill-posedness of the high-dimensional nonlinear problem. Phantom experiments with heterogeneous targets at different edge-to-edge distances demonstrate that SG

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“…The breakthrough in computational methods regarding optical molecular imaging laid the foundation for its application in the biomedical discipline, especially for three-dimensional tomographic imaging because traditional planar optical imaging only requires accomplishing a simple overlay without consideration of complex inversion reconstruction. Before the study of computational methods, the appropriate light transfer model should be selected because it is the basis of follow-up programs [35][36][37]. It is well known that the radiative transfer equation (RTE) can accurately model light propagation in biological tissues, but it is computationally too expensive to be used in practical applications due to its integro-differential nature, especially for the complex heterogeneous organisms with irregular internal structure [35].…”

Section: Optical Molecular Imagingmentioning

confidence: 99%

Translational Research of Optical Molecular Imaging for Personalized Medicine

Qin¹,

Ma²,

Hui

2013

CMM

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In the medical imaging field, molecular imaging is a rapidly developing discipline and forms many imaging modalities, providing us effective tools to visualize, characterize, and measure molecular and cellular mechanisms in complex biological processes of living organisms, which can deepen our understanding of biology and accelerate preclinical research including cancer study and medicine discovery. Among many molecular imaging modalities, although the penetration depth of optical imaging and the approved optical probes used for clinics are limited, it has evolved considerably and has seen spectacular advances in basic biomedical research and new drug development. With the completion of human genome sequencing and the emergence of personalized medicine, the specific drug should be matched to not only the right disease but also to the right person, and optical molecular imaging should serve as a strong adjunct to develop personalized medicine by finding the optimal drug based on an individual's proteome and genome. In this process, the computational methodology and imaging system as well as the biomedical application regarding optical molecular imaging will play a crucial role. This review will focus on recent typical translational studies of optical molecular imaging for personalized medicine followed by a concise introduction. Finally, the current challenges and the future development of optical molecular imaging are given according to the understanding of the authors, and the review is then concluded.

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Galerkin-based meshless methods for photon transport in the biological tissue

Cited by 33 publications

References 29 publications

Recent methodology advances in fluorescence molecular tomography

Recent methodology advances in fluorescence molecular tomography

Self-guided reconstruction for time-domain fluorescence molecular lifetime tomography

Translational Research of Optical Molecular Imaging for Personalized Medicine

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