Andreas Fhager

Reconstruction Quality and Spectral Content of an Electromagnetic Time-Domain Inversion Algorithm

A tomographic time-domain reconstruction algorithm for solving the inverse electromagnetic problem is described. The application we have in mind is dielectric breast cancer detection but the results are of general interest to the field of microwave tomography. Reconstructions have been made from experimental and numerically simulated data for objects of different sizes in order to investigate the relation between the spectral content of the illuminating pulse and the quality of the reconstructed image. We have found that the spectral content is crucial for a successful reconstruction. The work has further shown that when imaging objects with different scale lengths it is an advantage to use a multiple step procedure. Low frequency content in the pulse is used to image the large structures and the reconstruction process then proceed by using higher frequency data to resolve small scale lengths. Good agreement between the results obtained from experimental data and simulated data has been achieved

Microwave-Based Stroke Diagnosis Making Global Prehospital Thrombolytic Treatment Possible

Here, we present two different brain diagnostic devices based on microwave technology and the associated two first proof-of-principle measurements that show that the systems can differentiate hemorrhagic from ischemic stroke in acute stroke patients, as well as differentiate hemorrhagic patients from healthy volunteers. The system was based on microwave scattering measurements with an antenna system worn on the head. Measurement data were analyzed with a machine-learning algorithm that is based on training using data from patients with a known condition. Computer tomography images were used as reference. The detection methodology was evaluated with the leave-one-out validation method combined with a Monte Carlo-based bootstrap step. The clinical motivation for this project is that ischemic stroke patients may receive acute thrombolytic treatment at hospitals, dramatically reducing or abolishing symptoms. A microwave system is suitable for prehospital use, and therefore has the potential to allow significantly earlier diagnosis and treatment than today.

Using a priori Data to Improve the Reconstruction of Small Objects in Microwave Tomography

A study is presented where the use of dielectric a priori data in the reconstruction algorithm for microwave tomography is investigated. A new algorithm has been developed that includes the a priori dielectric data in the reconstruction process. This development is made as an extension to a conventional conjugate-gradient reconstruction algorithm. This paper further contains a numerical study of the new algorithm where the results indicate that by taking the a priori data into account, the accuracy and ability to resolve small objects can significantly be improved. This study was motivated by the development of an application for biomedical microwave imaging where it is investigated how knowledge of the tissue properties being imaged potentially can be used to improve the accuracy in the reconstruction.

Experimental Investigation of the Accuracy of an Ultrawideband Time-Domain Microwave-Tomographic System

The measurement accuracy of an ultrawideband (UWB) time-domain microwave-tomographic system is investigated. In order to make an assessment of the random variation of the measurements, the measurement repeatability of the system is evaluated by comparison with an UWB frequency-domain system. A phantom is imaged with the time-domain microwave-tomographic system, and the reconstructed images are compared with those obtained by using the frequency-domain system. The results suggest that with the averaging tens of measurements, the time-domain system can achieve the same level of measurement repeatability as that of the frequency-domain system in the interesting frequency range of microwave tomography. The imaging results, however, indicate that the phantom reconstruction does not require such high measurement accuracy. The permittivity profile of the phantom reconstructed from the nonaveraging time-domain measurements is very similar with that obtained by means of the frequency-domain system.

Experimental Investigation of an Optimization Approach to Microwave Tomography

Microwave imaging is an interesting and growing research field with a number of medical applications. This paper is based on the first series of experimental results using an iterative gradient algorithm based on the finite difference time domain (FDTD) method and synthetic pulses. Using our method, the permittivity and conductivity of an object are reconstructed layer by layer by minimizing a functional consisting of the difference between the measured and calculated electric field surrounding the object. This is done by surrounding the object with a number of antennas which are all in turn transmitting and receiving. The dielectric profiles used in the calculations are then iteratively updated until the functional is minimized. Results are presented demonstrating the ability to detect metallic and dielectric material in air and water.

Accuracy Evaluation of Ultrawideband Time Domain Systems for Microwave Imaging

We perform a theoretical analysis of the measurement accuracy of ultrawideband time domain systems. The theory is tested on a specific ultrawideband system and the analytical estimates of measurement uncertainty are in good agreements with those obtained by means of simulations. The influence of the antennas and propagation effects on the measurement accuracy of time domain near field microwave imaging systems is discussed. As an interesting application, the required measurement accuracy for a breast cancer detection system is estimated by studying the effect of noise on the image reconstructions. The results suggest that the effects of measurement errors on the reconstructed images are small when the amplitude uncertainty and phase uncertainty of measured data are less than 1.5 dB and 15 degrees, respectively.

Image Reconstruction in Microwave Tomography Using a Dielectric Debye Model

In this paper, quantitative dielectric image reconstruction based on broadband microwave measurements is investigated. A time-domain-based algorithm is derived where Debye model parameters are reconstructed in order to take into account the strong dispersive behavior found in biological tissue. The algorithm is tested with experimental and numerical data in order to verify the algorithm and to investigate improvements in the reconstructed image resulting from the improved description of the dielectric properties of the tissue when using broadband data. The comparison is made in relation to the more commonly used conductivity model. For the evaluation, two examples were considered, the first was a lossy saline solution and the second was less lossy tap water. Both liquids are strongly dispersive and used as a background medium in the imaging examples. The results show that the Debye model algorithm is of most importance in the tap water for a bandwidth of more than 1.5 GHz. Also the saline solution exhibits a dispersive behavior but since the losses restrict the useful bandwidth, the Debye model is of less significance even if somewhat larger and stronger artifacts can be seen in the conductivity model reconstructions.

3D Image Reconstruction in Microwave Tomography Using an Efficient FDTD Model

This letter describes an efficient three-dimensional (3D) image reconstruction algorithm for microwave tomography. Using the thin-wire approximation with resistive voltage sources (RVS), a realistic FDTD model is created for the transmitting and receiving antennas. To verify the algorithm, image reconstruction is made from experimental data using a cylindrical test object made of sunflower oil. In the results, successful image reconstruction has been shown, indicating that the FDTD model is applicable. For comparison, a reconstruction with a two-dimensional (2D) version of the algorithm was made. A significant increase in accuracy of the reconstructed object was seen for the 3D version.

A systematic approach to robust preconditioning for gradient-based inverse scattering algorithms

This paper presents a systematic approach to robust preconditioning for gradient-based nonlinear inverse scattering algorithms. In particular, one- and two-dimensional inverse problems are considered where the permittivity and conductivity profiles are unknown and the input data consist of the scattered field over a certain bandwidth. A time-domain least-squares formulation is employed and the inversion algorithm is based on a conjugate gradient or quasi-Newton algorithm together with an FDTD-electromagnetic solver. A Fisher information analysis is used to estimate the Hessian of the error functional. A robust preconditioner is then obtained by incorporating a parameter scaling such that the scaled Fisher information has a unit diagonal. By improving the conditioning of the Hessian, the convergence rate of the conjugate gradient or quasi-Newton methods are improved. The preconditioner is robust in the sense that the scaling, i.e. the diagonal Fisher information, is virtually invariant to the numerical resolution and the discretization model that is employed. Numerical examples of image reconstruction are included to illustrate the efficiency of the proposed technique.

Development of a Time Domain Microwave System for Medical Diagnostics

In this paper, a time-domain system dedicated to medical diagnostics has been designed, a prototype has been built and its performance has been evaluated. Measurements show that the system has a 3-dB bandwith of about 3.5 GHz and a signal to noise ratio over 40 dB in the frequency range about 800 MHz to 3.8 GHz. The system has been used to perform a microwave tomographic image reconstruction test. The same target was reconstructed based on data measured with a network analyzer. A comparison between the images shows very small differences, and proves the functionality of the time domain system.