Application of improved genetic algorithm to the noninvasive measurement of thermal parameters for living tissues
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摘要: 針對生物活體組織的多個熱特性參數同時測量的難點問題,提出了采用遺傳算法同時估計多個活體組織熱特性參數的方法,設計了實數編碼的遺傳算法.通過對選擇、交叉和突變算子進行改進,并引入小生境策略,提高了遺傳算法的全局尋優能力和搜索效率.對動態體模和人體前臂的熱特性參數測量的模擬仿真研究和實驗研究表明,采用改進的遺傳算法,能夠以較高的精度同時估計生物活體組織的多個熱特性參數.Abstract: The simultaneous measurement of multiple thermal parameters of living tissues is of great significance for medical clinical applications. A parameter estimation method using improved genetic algorithm (GA) was proposed to simultaneously estimate the multiple thermal parameters of living tissues. In the method the real-coded GA was designed, the selection, crossover and mutation operators were improved, and the niche mechanism was applied to improve the capability of global optimization. The simulation and experimental researches of a dynamic phantom and a human forearm indicate that it is feasible and effective to simultaneously estimate the multiple thermal parameters of living tissues with high accuracy by the proposed method.
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Key words:
- bioheat transfer /
- blood perfusion /
- genetic algorithm /
- parameter estimation /
- thermal conductivity
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