No 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.

The authors found a significant improvement in the contrast detectability performance of CT imaging when complemented with functional imaging information from EIT. Along with the feature assessment metrics, the concept of complementing CT with EIT imaging can lead to an EIT/CT imaging modality which might fully utilize the functional imaging abilities of EIT imaging, thereby enhancing the quality of care in the areas of cancer diagnosis and radiotherapy treatment planning.

The aim of this paper is to represent a method where a blind person can get information about the shape of an image through speech signal. In this paper we proposed an algorithm for image recognition by speech sound. Blind people face a number of challenges when interacting with their environments because so much information is encoded visually. The proposed method enables the visually impaired people to see with the help of ears. The novelty of this paper is to convert the image to sound using the methodology of edge detection.

Purpose:Multi‐frequency EIT has been reported to be a potential tool in distinguishing a tissue anomaly from background. In this study, we investigate the feasibility of acquiring functional information by comparing multi‐frequency EIT images in reference to the structural information from the CT image through fusion.Methods:EIT data was acquired from a slice of winter melon using sixteen electrodes around the phantom, injecting a current of 0.4mA at 100, 66, 24.8 and 9.9 kHz. Differential EIT images were generated by considering different combinations of pair frequencies, one serving as reference data and the other as test data. The experiment was repeated after creating an anomaly in the form of an off‐centered cavity of diameter 4.5 cm inside the melon. All EIT images were reconstructed using Electrical Impedance Tomography and Diffuse Optical Tomography Reconstruction Software (EIDORS) package in 2‐D differential imaging mode using one‐step Gaussian Newton minimization solver. CT image of the melon was obtained using a Phillips CT Scanner. A segmented binary mask image was generated based on the reference electrode position and the CT image to define the regions of interest. The region selected by the user was fused with the CT image through logical indexing.Results:Differential images based on the reference and test signal frequencies were reconstructed from EIT data. Result illustrated distinct structural inhomogeneity in seeded region compared to fruit flesh. The seeded region was seen as a higherimpedance region if the test frequency was lower than the base frequency in the differential EIT reconstruction. When the test frequency was higher than the base frequency, the signal experienced less electrical impedance in the seeded region during the EIT data acquisition.Conclusion:Frequency‐based differential EIT imaging can be explored to provide additional functional information along with structural information from CT for identifying different tissues.