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首页> 外文会议>IEEE MTT-S International Microwave Biomedical Conference >Comparison of two global optimization techniques for hyperthermia treatment planning of breast cancer: Coupled electromagnetic and thermal simulation study
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Comparison of two global optimization techniques for hyperthermia treatment planning of breast cancer: Coupled electromagnetic and thermal simulation study

机译：乳腺癌热疗治疗计划两种全局优化技术的比较：耦合电磁和热模拟研究

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The performance of the genetic algorithm (GA) and particle swarm optimization (PSO) was compared to identify the best-suited algorithm for hyperthermia treatment planning (HTP) of breast cancer. Both algorithms were tested on four heterogeneous patient breast models derived from magnetic resonance (MR) images. Electromagnetic (EM) simulations indicate that PSO induces 5.7% less hotspot to target quotient (HTQ) compared to GA. However, coupled EM and thermal simulations of four patient models indicate that GA based HTP induces $oldsymbol{1.25}^{circ} mathbf{C}-oldsymbol{3.87}^{circ}mathbf{C}$ higher average temperature in cancer tissue with limited thermal hotspots in healthy tissue when compared to PSO algorithm. This was observed to be due to the low power level assigned to each channel by PSO compared to GA. Coupled simulations of heterogeneous patient models indicate GA is a better global optimization algorithm for HTP of breast cancer.
机译：比较遗传算法（GA）和粒子群优化（PSO）的性能，以鉴定乳腺癌的热疗治疗计划（HTP）最适合算法。在源自磁共振（MR）图像的四种异质患者乳房模型上测试了这两种算法。电磁（EM）模拟表明，与GA相比，PSO将距离目标（HTQ）减少5.7％。但是，四个患者模型的耦合EM和热模拟表明GA基HTP诱导 $ boldsymbol {1.25} ^ { rIC} mathbf {c} - boldsymbol {3.87} ^ { cir} mathbf {c} $ 与PSO算法相比，在健康组织中具有有限的热热点的癌症组织的平均温度较高。观察到这是由于与GA相比，PSO分配给每个通道的低功率水平。异质患者模型的耦合模拟表明GA是乳腺癌HTP的更好的全局优化算法。

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