Conductivity Reconstruction of Brain Edema Based on Improved Adaptive Genetic Algorithm

In order to estimate the progression or regression of edema at the bedside continuously, based the theoretic model, an improved Adaptive Genetic Algorithm(AGA) has been applied in optimization of conductivity reconstruction. Dynamic crossover and mutation operators, which are based on Maiming Distan...

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Bibliographic Details
Main Authors: Jicheng Liu, Kama Huang, Yayi Hu, Qing Chen
Format: Conference Proceeding
Language:English
Subjects:
Biomedical engineering
Brain modeling
Coils
Conductivity measurement
conductivity reconstruction
Eddy currents
edema
Frequency
Genetic Algorithm
Genetic algorithms
Genetic mutations
Haiming Distance
Impedance
Mutual coupling
operator
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Summary:In order to estimate the progression or regression of edema at the bedside continuously, based the theoretic model, an improved Adaptive Genetic Algorithm(AGA) has been applied in optimization of conductivity reconstruction. Dynamic crossover and mutation operators, which are based on Maiming Distance, are brought forward in this paper to maintain generation's diversity. As a contrast, the Simple GA(SGA) has also been applied in same optimization of brain edema. It is shown the AGA not only has satisfied efficiency but also has enhanced the capability to converge to the best answer.
ISSN:1948-2914
1948-2922
DOI:10.1109/BMEI.2008.53