Light transport in turbid media with non-scattering, low-scattering and high absorption heterogeneities based on hybrid simplified spherical harmonics with radiosity model

Yang, Defu; Chen, Xueli; Peng, Zhen; Wang, Xiaorui; Ripoll, Jorge; Wang, Jing; Liang, Jimin

doi:10.1364/boe.4.002209

Cited by 17 publications

(17 citation statements)

References 37 publications

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“…However, they are either limited by using RTE (Tarvainen 2005, Gorpas et al 2010, Lehtikangas et al 2013 or proposed for the problem of light propagation in void regions (Firbank et al 1996, Dehghani et al 1999. In our previous study (Yang et al 2013), the hybrid SP N with radiosity model (HSRM) was proposed to describe light propagation in the turbid media with high, low scattering and high absorption as well as void region, but it still suffers the large computational burden and time cost of SP N .…”

Section: Introductionmentioning

confidence: 99%

Hybrid simplified spherical harmonics with diffusion equation for light propagation in tissues

et al. 2015

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Aiming at the limitations of the simplified spherical harmonics approximation (SPN) and diffusion equation (DE) in describing the light propagation in tissues, a hybrid simplified spherical harmonics with diffusion equation (HSDE) based diffuse light transport model is proposed. In the HSDE model, the living body is first segmented into several major organs, and then the organs are divided into high scattering tissues and other tissues. DE and SPN are employed to describe the light propagation in these two kinds of tissues respectively, which are finally coupled using the established boundary coupling condition. The HSDE model makes full use of the advantages of SPN and DE, and abandons their disadvantages, so that it can provide a perfect balance between accuracy and computation time. Using the finite element method, the HSDE is solved for light flux density map on body surface. The accuracy and efficiency of the HSDE are validated with both regular geometries and digital mouse model based simulations. Corresponding results reveal that a comparable accuracy and much less computation time are achieved compared with the SPN model as well as a much better accuracy compared with the DE one.

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Section: Introductionmentioning

confidence: 99%

Hybrid simplified spherical harmonics with diffusion equation for light propagation in tissues

et al. 2015

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“…The known features of computational models and simulated datasets provide precise information enabling to evaluate the impact of physical degrading factors inherent to the imaging process, [131][132][133][134][135] assess different design concepts and performance of medical imaging systems, [136][137][138][139][140][141][142][143][144][145][146][147][148][149][150] and advance the development and validation of new image segmentation, [151][152][153][154][155] registration, 156-161 reconstruction, [162][163][164][165][166][167] and processing techniques. [168][169][170][171][172][173][174][175] Likewise, the Digimouse and MOBY models served as optically heterogeneous virtual subjects for light propagation calculations to assess the impact of various parameters involved in optical molecular imaging techniques [176][177][178][179][180]…”

Section: C Medical Imaging Physicsmentioning

confidence: 99%

Development of computational small animal models and their applications in preclinical imaging and therapy research

Xie

Zaidi

2015

Med. Phys.

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The development of multimodality preclinical imaging techniques and the rapid growth of realistic computer simulation tools have promoted the construction and application of computational laboratory animal models in preclinical research. Since the early 1990s, over 120 realistic computational animal models have been reported in the literature and used as surrogates to characterize the anatomy of actual animals for the simulation of preclinical studies involving the use of bioluminescence tomography, fluorescence molecular tomography, positron emission tomography, single-photon emission computed tomography, microcomputed tomography, magnetic resonance imaging, and optical imaging. Other applications include electromagnetic field simulation, ionizing and nonionizing radiation dosimetry, and the development and evaluation of new methodologies for multimodality image coregistration, segmentation, and reconstruction of small animal images. This paper provides a comprehensive review of the history and fundamental technologies used for the development of computational small animal models with a particular focus on their application in preclinical imaging as well as nonionizing and ionizing radiation dosimetry calculations. An overview of the overall process involved in the design of these models, including the fundamental elements used for the construction of different types of computational models, the identification of original anatomical data, the simulation tools used for solving various computational problems, and the applications of computational animal models in preclinical research. The authors also analyze the characteristics of categories of computational models (stylized, voxel-based, and boundary representation) and discuss the technical challenges faced at the present time as well as research needs in the future. C 2016 American Association of Physicists in Medicine. [http://dx

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“…12 Hybrid models combine diffusion theory to calculate bulk-features of the light transport with ray-tracing to propagate photons in the void regions. 11,[13][14][15] Transport theory, from which diffusion theory is derived, is a more generally accurate means to model NIR light transport in complex systems. 16,17 Monte Carlo methods, particularly with transport-based engines, can also be applied.…”

Section: Light Propagation Modeling In the Human Headmentioning

confidence: 99%

Monte Carlo modeling of light propagation in the human head for applications in sinus imaging

et al. 2015

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Abstract. Sinus blockages are a common reason for physician visits, affecting one out of seven people in the United States, and often require medical treatment. Diagnosis in the primary care setting is challenging because symptom criteria (via detailed clinical history) plus objective imaging [computed tomography (CT) or endoscopy] are recommended. Unfortunately, neither option is routinely available in primary care. We previously demonstrated that low-cost near-infrared (NIR) transillumination correlates with the bulk findings of sinus opacity measured by CT. We have upgraded the technology, but questions of source optimization, anatomical influence, and detection limits remain. In order to begin addressing these questions, we have modeled NIR light propagation inside a three-dimensional adult human head constructed via CT images using a mesh-based Monte Carlo algorithm (MMCLAB). In this application, the sinus itself, which when healthy is a void region (e.g., nonscattering), is the region of interest. We characterize the changes in detected intensity due to clear (i.e., healthy) versus blocked sinuses and the effect of illumination patterns. We ran simulations for two clinical cases and compared simulations with measurements. The simulations presented herein serve as a proof of concept that this approach could be used to understand contrast mechanisms and limitations of NIR sinus imaging. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Light transport in turbid media with non-scattering, low-scattering and high absorption heterogeneities based on hybrid simplified spherical harmonics with radiosity model

Cited by 17 publications

References 37 publications

Hybrid simplified spherical harmonics with diffusion equation for light propagation in tissues

Hybrid simplified spherical harmonics with diffusion equation for light propagation in tissues

Development of computational small animal models and their applications in preclinical imaging and therapy research

Monte Carlo modeling of light propagation in the human head for applications in sinus imaging

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