title: Breast cancer detection based on multi-frequency EIS measurement.
abstract: As a convenient, un-injurious and low cost method for women breast tumor diagnosis, Electrical Impedance Scanning (EIS) is being paid increasing attention. But EIS still has some problems. In theory the malignant tumor has higher electrical conductivity than normal tissue and benign tumor, so the cancer will be recognized in the EIS image as a bright spot. However, in practical the difference is not so obvious. In many cases it is difficult to judge whether a suspicious bright spot tells a malignant or benign tumor. This paper concerns a new method based on multi-frequency EIS measurement to solve this problem. A group of scanning results with various stimulating frequencies will be performed during an EIS measurement, which is automatically controlled by specially designed device and the location and pressure of the sensor will keep stable, so we will get a series of data at different stimulating frequencies through a measurement. Because the malignant and the benign tumor have different curves in electrical conductivity-frequency diagram, we can analyze the data at every frequency and find out the attribute of the tumor. Clinical trails have been carried out. Subjects were suspicious sufferers that were to receive histopathology examinations, and all analyses have been compared with histopathology results.
authors.affiliation: Fourth Military Medical University, Xi'an, China. dyryzxq@fmmu.edu.cn
authors.forename: Zhen
authors.initials: Z
authors.lastname: Cheng
authors.forename: Dong
authors.initials: D
authors.lastname: Xiuzhen
authors.forename: Fu
authors.initials: F
authors.lastname: Feng
authors.forename: Ji
authors.initials: J
authors.lastname: Zhenyu
authors.forename: Xu
authors.initials: X
authors.lastname: Canhua
mesh_terms: D001940:Breast / Q000473:pathology*; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000473:pathology; D002986:Clinical Trials as Topic; D017097:Electric Impedance; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D011237:Predictive Value of Tests