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In this paper, we introduce a novel microwave tomography system, which utilizes 24 double-layered Vivaldi antennas, each of which is equipped with a diode-loaded printed-wire probe. By biasing the probe's diodes, the impedance of the probe is modified, allowing an indirect measurement of the electric field at the probe's locations. Each printed-wire probe is loaded with five equally spaced p-i-n diodes, in series. We show that electric field data collected in this way within the proposed tomography system can be used to reconstruct the dielectric properties of an object of interest. Reconstructions for various objects are shown. Although the results are still preliminary, sufficient experimentation has been done to delineate the advantages of such an indirect method of collecting scattered-field data for tomographic imaging purposes. [ABSTRACT FROM PUBLISHER]

Regularization methods are used in microwave image reconstruction problems, which are ill-posed. Traditional regularization methods are usually problem-independent and do not take advantage of a priori information specific to any particular imaging application. In this paper, a novel problem-dependent regularization approach is introduced for the application of breast imaging. A real genetic algorithm (RGA) minimizes a cost function that is the error between the recorded and the simulated data. At each iteration of the RGA, a priori information about the shape of the breast profiles is used by a neural network classifier to reject the solutions that cannot be a map of the dielectric properties of a breast profile. The algorithm was tested against four realistic numerical breast phantoms including a mostly fatty, a scattered fibroglandular, a heterogeneously dense, and a very dense sample. The tests were also repeated where a 4 mm \times 4 mm tumor was inserted in the fibroglandular tissue in each of the four breast types. The results show the effectiveness of the proposed approach, which to the best of our knowledge has the highest resolution amongst the evolutionary algorithms used for the inversion of realistic numerical breast phantoms. [ABSTRACT FROM PUBLISHER]

In this paper, we describe a 2-D wideband microwave imaging system intended for biomedical imaging. The system is capable of collecting data from 3 to 6 GHz, with 24 coresident antenna elements connected to a vector network analyzer via a 2 x 24 port matrix switch. As one of the major sources of error in the data collection process is a result of the strongly coupling 24 coresident antennas, we provide a novel method to avoid the frequencies where the coupling is large enough to prevent successful imaging. Through the use of two different nonlinear reconstruction schemes, which are an enhanced version of the distorted born iterative method and the multiplicative regularized contrast source inversion method, we show imaging results from dielectric phantoms in free space. The early inversion results show that with the frequency selection procedure applied, the system is capable of quantitatively reconstructing dielectric objects, and show that the use of the wideband data improves the inversion results over single-frequency data. [ABSTRACT FROM AUTHOR]

The article focuses on the measurement techniques and the numerical simulations that were involved in a study conducted to present improved permittivity measurement techniques for circular dielectric disk and annular samples through coaxial transmission line fixtures. It discusses a new method to measure the permittivity of annular samples using quadratic curve fitting. It examines the results of the sensitivity analyses and preliminary experiment regarding the quadratic curve fitting method.