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  • Author: Kirpal Kohli x
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Electrical characterization of bolus material as phantom for use in electrical impedance and computed tomography fusion imaging

Abstract

Phantoms are widely used in medical imaging to predict image quality prior to clinical imaging. This paper discusses the possible use of bolus material, as a conductivity phantom, for validation and interpretation of electrical impedance tomography (EIT) images. Bolus is commonly used in radiation therapy to mimic tissue. When irradiated, it has radiological characteristics similar to tissue. With increased research interest in CT/EIT fusion imaging there is a need to find a material which has both the absorption coefficient and electrical conductivity similar to biological tissues. In the present study the electrical properties, specifically resistivity, of various commercially available bolus materials were characterized by comparing their frequency response with that of in-vivo connective adipose tissue. It was determined that the resistivity of Gelatin Bolus is similar to in-vivo tissue in the frequency range 10 kHz to 1MHz and therefore has potential to be used in EIT/CT fusion imaging studies.

Open access
Cancer detection based on electrical impedance spectroscopy: A clinical study

Abstract

An electrical Impedance based tool is designed and developed to aid physicians performing clinical exams focusing on cancer detection. Current research envisions improvement in sensor-based measurement technology to differentiate malignant and benign lesions in human subjects. The tool differentiates malignant anomalies from nonmalignant anomalies using Electrical Impedance Spectroscopy (EIS). This method exploits cancerous tissue behavior by using EIS technique to aid early detection of cancerous tissue.

The correlation between tissue electrical properties and tissue pathologies is identified by offering an analysis technique based on the Cole model. Additional classification and decision-making algorithm is further developed for cancer detection. This research suggests that the sensitivity of tumor detection will increase when supplementary information from EIS and built-in intelligence are provided to the physician.

Open access