Research on Three-dimensional Temperature Field Reconstruction in Biological Tissue Based on Multi-island Genetic Algorithm_Journal of Biomedical Engineering

Authors：

YEFuli ¹ , LIKaiyang ^1,2 ,  SHIGuilian ^1,2

1. School of Biomedical Engineering, Hubei University of Science and Technology, Xianning 437100, China;
2. School of Physics and Technology, Wuhan University, Wuhan 430072, China;

Corresponding author：

SHIGuilian, Email: shiguilian@163.com

Keywords：

multi-island genetic algorithm; three-dimensional temperature field; target function; integrated optimization

DOI：

10.7507/1001-5515.20160110

Video：

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Abstract Full text Figures/Tables Video References Cited by

The nondestructive reconstruction of three-dimensional (3D) temperature field in biological tissue is always an important problem to be resolved in biomedical engineering field. This paper presents a novel method of nondestructive reconstruction of 3D temperature field in biological tissue based on multi-island genetic algorithm (MIGA). By this method, the resolving of inverse problem of bio-heat transfer is transformed to be a solving process of direct problem. An experiment and its corresponding simulation were carried out to verify the feasibility and reliability. In the experiment a high purity polypropylene material, whose thermophysical parameters were similar to the fat tissue being tested, were adopted so that it could avoid the negative results created by the other factors. We set the position P(x, y, z) as the point heat source in the biological tissue and its temperature t as optimization variable, got the experimental temperature values of the points in a module surface, subtracted them from the corresponding simulating temperature values in the same module surface, and then took the sum of absolute value. We took it as the objective function of successive iteration. It was found that the less the target value was, the more optimal the current variables, i.e. the heat source position and the temperature values, were. To improve the optimization efficiency, a novel establishment method of objective function was also provided. The simulating position and experimental position of heat source were very approximate to each other. When the optimum values are determined, the corresponding 3D temperature field is also confirmed, and the temperature distribution of arbitrary section can be acquired. The MIGA can be well applied in the reconstruction of 3D temperature field in biological tissue. Because of the differences between the MIGA and the traditional numerical methods, we do not have to acquire all the data of surface. It is convenient and fast, and shows a prosperous application future.

Citation： YEFuli, LIKaiyang, SHIGuilian. Research on Three-dimensional Temperature Field Reconstruction in Biological Tissue Based on Multi-island Genetic Algorithm. Journal of Biomedical Engineering, 2016, 33(4): 666-673. doi: 10.7507/1001-5515.20160110 Copy

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1. 马国军, 江国泰, 孙兵.生物组织传热红外热成像的三维温度场重建[J].中国组织工程研究与临床康复, 2010, 14(30):5614-5617.
2. 邢键, 万雄, 孙晓刚, 等.CCD光谱层析技术重建氩等离子束射流三维温度场[J].光谱学与光谱分析, 2009, 29(11):3023-3027.
3. DAS K, MISHRA S C. Estimation of tumor characteristics in a breast tissue with known skin surface temperature[J]. J Therm Biol, 2013, 38(6):311-317.
4. 张志敏, 常方飞, 张辉.发射光谱层析重建温度场中的温度定标[J].光电技术应用, 2009, 24(1):5-8.
5. 孙小平, 田丰, 邵富群, 等.复杂温度场图像重建算法实验研究[J].东北大学学报, 2006, 27(3):268-271.
6. CARLUCCIO G, ERRICOLO D, OH S, et al. An approach to rapid calculation of temperature change in tissue using spatial filters to approximate effects of thermal conduction[J]. IEEE Trans Biomed Eng, 2013, 60(6):1735-1741.
7. MICHEL A P, LIAKAT S, BORS K, et al. In vivo measurement of mid-infrared light scattering from human skin[J]. Biomed Opt Express, 2013, 4(4):520-530.
8. LUCASSEN G W, VAN VEEN G N, JANSEN J A. Band analysis of hydrated human skin stratum corneum attenuated total reflectance fourier transform infrared spectra in vivo[J]. J Biomed Opt, 1998, 3(3):267-280.
9. CHEN Hongtao, WANG Haifeng, SLIPCHENKO M N, et al. A multimodal platform for nonlinear optical microscopy and microspectroscopy[J]. Opt Express, 2009, 17(3):1282-1290.
10. 张军挪, 王瑞林, 尚利民, 等.改进遗传算法和有限元计算相结合的优化方法研究[J].兵工学报, 2010, 31(2):135-138.
11. JAMIL M, NG E Y K. Ranking of parameters in bioheat transfer using Taguchi analysis[J]. International Journal of Thermal Sciences, 2013, 63:15-21.
12. OKAJIMA J, MARUYAMA S, TAKEDA H, et al. Dimensionless solutions and general characteristics of bioheat transfer during thermal therapy[J]. J Therm Biol, 2009, 34(8):377-384.
13. BHOWMIK A, SINGH R, REPAKA R, et al. Conventional and newly developed bioheat transport models in vascularized tissues:A review[J]. J Therm Biol, 2013, 38(3):107-125.
14. 李守巨, 刘迎曦.改进遗传算法在非线性热传导参数识别中的应用[J].工程力学, 2005, 22(3):72-75, 87.

Journal of Biomedical Engineering

Research on Three-dimensional Temperature Field Reconstruction in Biological Tissue Based on Multi-island Genetic Algorithm

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