Recognition Method Of Breast Tissues Based On BP Network Using Bio-impedance Information

Bio-Impedance Measuring Technology (BIMT) is a noninvasive measuring technology, the purpose of which is to extract physiological and pathological information by detecting the electrical properties of tissues and organs. It has the feature of low-cost, safety, easy-operating and wealth of information. So it is been paid special attention by the researchers in clinical medicine areas.Based on the bio-impedance measurement technology, this paper presents the intraoperative margin assessment of breast cancer for purpose of breast conserving surgery. It can help the surgeon judge the margin instantly and then choose the excising area reasonably. So that the remained focus could be cleaned in time. It can shorten the waiting time and lighten patients'pain in partial mastectomy.This paper focuses on researching the differences of electrical properties between breast cancer and normal breast tissues (mammary gland and adipose). The characteristic parameters searched from the frequency-resistance curve were studied to distinguish different tissues. Based on the analysis of clinical data, frequency-resistance slope information was found good enough to be used in the recognition of breast tissues. This paper utilized the slopes of special frequencies and multi- frequencies to identify three different tissues. Because of the multi-parameters, uncertain model and so on, the BP network was established and the integration of several neural networks was researched to recognize breast tissues.Results of the research indicated that BP network had good capability of classification while there were many input parameters. BP networks trained for many times have nice abilities to distinguish breast cancer from normal tissues. The integral neural network possessed high sensibility and specificity to the recognition of breast tissues.