一种电阻抗频谱法自动诊断乳腺组织疾病优化算法研究

doi:10.3969/j.issn.0258-8021.2013.02.005

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Abstract It is very important to make early diagnosis with breast tissue disease. The method based on Electrical Impedance Spectroscopy is effective for the clinical diagnosis. Advantages of the method include lowcost and nondamage. In this paper, we focused on the early automatic diagnosis of breast tissue disease based on two intelligent classifiers; BP network and support vector machine (SVM). The data of Electrical Impedance Spectroscopy come from 64 subjects, including 106 breast tissue samples. Focus on the uncertain property of selecting characters of the classifiers, parameter optimization and selecting were conducted based on the Genetic Algorithm. Based on principle of the overall optimization and the survival of the fittest, selectioncrossovermutation was done to pursue the optical parameters. After the process, the accuracy of automatic diagnosis was improved from 61.9% and 51.9% to 76.2% and 68.0%. The method is expected to provide an effectual method for the clinical automatic diagnosis of breast tissue disease.

Key words： automatic diagnosis of breast tissue disease electrical impedance spectroscopy method genetic algorithm support vector machine (SVM) BP neural network

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	Articles by authors
	LI Xin¹
	2*LI Hong Hong¹
	2LI Cong¹
	2LI Chang Wu^3

Cite this article:

LI Xin^1,2*LI Hong Hong^1,2LI Cong^{1, et al. An Optimization Algorithm of Automatic Diagnosis of Breast[J]. journal1, 2013, 32(2): 154-160.}

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http://cjbme.csbme.org/EN/10.3969/j.issn.0258-8021.2013.02.005 OR http://cjbme.csbme.org/EN/Y2013/V32/I2/154

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