
doi: 10.1007/bf02344684
pmid: 10829386
Electrical impedance spectroscopy is a minimally invasive technique that has clear advantages for living tissue characterisation owing to its low cost and ease of use. The present paper describes how this technique can be applied to breast tissue classification and breast cancer detection. Statistical analysis is used to derive a set of rules based on features extracted from the graphical representation of electrical impedance spectra. These rules are used hierarchically to discriminate several classes of breast tissue. Results of statistical classification obtained from a data set of 106 cases representing six classes of excised breast tissue show an overall classification efficiency of approximately 92% with carcinoma discrimination > 86%.
Electrodiagnosis, Electric Impedance, Discriminant Analysis, Humans, Breast Neoplasms, Female, Signal Processing, Computer-Assisted
Electrodiagnosis, Electric Impedance, Discriminant Analysis, Humans, Breast Neoplasms, Female, Signal Processing, Computer-Assisted
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