Signal calibration for an electrical impedance mammography system

Electrical Impedance Tomography (EIT) technology has been applied clinically since the 1980s. Numerous papers have addressed a variety of systematic error sources and indicated different calibration methods. The Sussex Mk4 Electrical Impedance Mammography (EIM) system has been developed for the investigation of early stage breast lesions. Investigations have shown that the system performance is subjected to a number of systematic errors: frequencies-dependant noise level due to both internal and external sources; stray capacitance within both PCB tracks and cable connections; and artefacts generated by patient movement during scanning etc. This paper reports upon several traditional and novel calibration methods utilized to reduce some of these errors in the acquired signals before image reconstruction. Techniques used include frequency spectrum analysis, filtering, phase calibration and other means of noise reduction. Results of both before and after calibration are presented and analyzed. The conclusion is reached that the signal quality of the Sussex Mk4 EIM system is such that the system is, post-calibrated, capable of producing images for the diagnosis of breast cancer

A flexible and configurable hardware for the combined EIM and Ultrasound device

One of the current methods in breast cancer detection is Sonography, also known as Ultrasound imaging. Sonography is effective for imaging soft tissues of the body and returns a high resolution image. Its operation is highly subjective depending on the operator and the images do vary with positioning. At the University of Sussex we have successfully built an automated and repeatable Ultrasound scanner and combined and reconstructed the data in 3D. Ultrasound imaging does have its limitations when it comes to cancer detection and diagnosis. The Sussex EIM (Electrical Impedance Mammography) device is a novel imaging system developed at the University of Sussex for the detection of breast lesions in-vivo using quadrature detection of impedance. Combining the high resolution images of Ultrasound with the parametric data of EIT would give a more precise diagnosis. This paper describes how we have achieved a totally configurable system where we have combined our current EIT technology for breast cancer detection to the 3D Ultrasound scanner we have built. This was done with a quick turn-around in development time using off-the-shelf hardware and a 3U PXI Chassis. The system is based around a National Instruments PXI (PCI eXtensions for Instrumentation) chassis which is a modular electronic instrumentation platform