Adaptively Hybrid $3^{\text{rd}}$  Simplified Spherical Harmonics With Diffusion Equation-Based Multispectral Cerenkov Luminescence Tomography

Wang, Lin; Cao, Honghao; Cao, Xin; Ren, Shenghan; Li, Ké; Zhan, Yonghua; Chen, Xueli; He, Xiaowei

doi:10.1109/access.2019.2950265

Cited by 4 publications

(3 citation statements)

References 47 publications

(45 reference statements)

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“…and Wang et al. applied the HSDE model as the forward imaging model for fluorescence molecular tomography ( 28 ), multispectral Cerenkov luminescence tomography ( 53 ), and X-ray luminescence computed tomography ( 54 ), respectively. The concise form of the HSDE model can be expressed as ( 29 ):…”

Section: Light Propagation Modelsmentioning

confidence: 99%

Harnessing the Power of Hybrid Light Propagation Model for Three-Dimensional Optical Imaging in Cancer Detection

et al. 2021

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Optical imaging is an emerging technology capable of qualitatively and quantitatively observing life processes at the cellular or molecular level and plays a significant role in cancer detection. In particular, to overcome the disadvantages of traditional optical imaging that only two-dimensionally and qualitatively detect biomedical information, the corresponding three-dimensional (3D) imaging technology is intensively explored to provide 3D quantitative information, such as localization and distribution and tumor cell volume. To retrieve these information, light propagation models that reflect the interaction between light and biological tissues are an important prerequisite and basis for 3D optical imaging. This review concentrates on the recent advances in hybrid light propagation models, with particular emphasis on their powerful use for 3D optical imaging in cancer detection. Finally, we prospect the wider application of the hybrid light propagation model and future potential of 3D optical imaging in cancer detection.

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Section: Light Propagation Modelsmentioning

confidence: 99%

Harnessing the Power of Hybrid Light Propagation Model for Three-Dimensional Optical Imaging in Cancer Detection

et al. 2021

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“…The homogenous model is relatively simple, and is quite different from the real imaging organisms, resulting in inaccurate results. This can be solved by more complex heterogeneous model ( 8 , 9 , 11 , 14 , 15 ). However, due to the serious morbidity of CLT reconstruction, the quality of the reconstructed images needs to be further improved.…”

Section: Introductionmentioning

confidence: 99%

“…This problem can be solved by its 3D derivatives, namely the Cerenkov luminescence tomography (CLT). CLT reconstructs the spatial distribution of the internal radionuclide probes by integrating the CL images measured from the body surface with the structural information and other prior information (7)(8)(9)(10)(11)(12)(13). Li et al first proposed the concept of CLT, reconstructing the 3D distribution of 18 FDG in a homogeneous mouse model (8).…”

Section: Introductionmentioning

confidence: 99%

Prior Compensation Algorithm for Cerenkov Luminescence Tomography From Single-View Measurements

Wang

2021

Front. Oncol.

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Cerenkov luminescence tomography (CLT) has attracted much attention because of the wide clinically-used probes and three-dimensional (3D) quantification ability. However, due to the serious morbidity of 3D optical imaging, the reconstructed images of CLT are not appreciable, especially when single-view measurements are used. Single-view CLT improves the efficiency of data acquisition. It is much consistent with the actual imaging environment of using commercial imaging system, but bringing the problem that the reconstructed results will be closer to the animal surface on the side where the single-view image is collected. To avoid this problem to the greatest extent possible, we proposed a prior compensation algorithm for CLT reconstruction based on depth calibration strategy. This method takes full account of the fact that the attenuation of light in the tissue will depend heavily on the depth of the light source as well as the distance between the light source and the detection plane. Based on this consideration, a depth calibration matrix was designed to calibrate the attenuation between the surface light flux and the density of the internal light source. The feature of the algorithm was that the depth calibration matrix directly acts on the system matrix of CLT reconstruction, rather than modifying the regularization penalty items. The validity and effectiveness of the proposed algorithm were evaluated with a numerical simulation and a mouse-based experiment, whose results illustrated that it located the radiation sources accurately by using single-view measurements.

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X‐ray luminescence computed tomography using a hybrid proton propagation model and Lasso‐LSQR algorithm

Guo

Zhao

et al. 2021

Journal of Biophotonics

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X‐ray luminescence computed tomography (XLCT) uses external X‐rays for luminescence excitation, which is becoming a promising molecular imaging technique with superb penetration depth and spatial resolution. To achieve the tomographic mapping of luminescence distribution, accurate optical propagation model and suitable reconstruction method are two keys for XLCT, but not satisfied. To overcome the limitation of the single proton propagation model (e.g., DE, SP3), we adopted a hybrid diffusion equation with third order simplified spherical harmonics (DE‐SP3) model for XLCT. To enable fast iteration and accurate sparse reconstruction, we also integrated in the inversion optimization, with a novel Least Square QR‐factorization based on the Lasso (Lasso‐LSQR) algorithm. We first simulated the light propagation in various kinds of organs under DE model and SP3 model, respectively. By comparison with the Monte Carlo, these tissues can be categorized into two types, namely DE‐fitted tissues that include muscle and lung, and SP3‐fitted tissues including heart, kidney, liver, and stomach. According to the above classification results, we built a hybrid DE‐SP3 model to more accurately describing light transport. Numerical simulations and in vivo experiments illustrated that hybrid DE‐SP3 model achieves superior reconstruction performance in terms of location accuracy, and spatial resolution than DE, and less computational cost than SP3. The hybrid DE‐SP3 model materializes a balance between accuracy and efficiency for XLCT.

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Adaptively Hybrid $3^{\text{rd}}$ Simplified Spherical Harmonics With Diffusion Equation-Based Multispectral Cerenkov Luminescence Tomography

Cited by 4 publications

References 47 publications

Harnessing the Power of Hybrid Light Propagation Model for Three-Dimensional Optical Imaging in Cancer Detection

Harnessing the Power of Hybrid Light Propagation Model for Three-Dimensional Optical Imaging in Cancer Detection

Prior Compensation Algorithm for Cerenkov Luminescence Tomography From Single-View Measurements

X‐ray luminescence computed tomography using a hybrid proton propagation model and Lasso‐LSQR algorithm

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