Quantitative interpretation of UWB radar images for non-invasive tissue temperature estimation during hyperthermia

The knowledge of temperature distribution inside the tissue to be treated is essential for patient safety, workflow and clinical outcomes of thermal therapies. Microwave imaging represents a promising approach for non-invasive tissue temperature monitoring during hyperthermia treatment. In the present paper, a methodology for quantitative non-invasive tissue temperature estimation based on ultra-wideband (UWB) radar imaging in the microwave frequency range is described. The capabilities of the proposed method are demonstrated by experiments with liquid phantoms and three-dimensional (3D) Delay-and-Sum beamforming algorithms. The results of our investigation show that the methodology can be applied for detection and estimation of the temperature induced dielectric properties change

Matrix pencil method for vital sign detection from signals acquired by microwave sensors

Microwave sensors have recently been introduced as high-temporal resolution sensors, which could be used in the contactless monitoring of artery pulsation and breathing. However, accurate and efficient signal processing methods are still required. In this paper, the matrix pencil method (MPM), as an efficient method with good frequency resolution, is applied to back-reflected microwave signals to extract vital signs. It is shown that decomposing of the signal to its damping exponentials fulfilled by MPM gives the opportunity to separate signals, e.g., breathing and heartbeat, with high precision. A publicly online dataset (GUARDIAN), obtained by a continuous wave microwave sensor, is applied to evaluate the performance of MPM. Two methods of bandpass filtering (BPF) and variational mode decomposition (VMD) are also implemented. In addition to the GUARDIAN dataset, these methods are also applied to signals acquired by an ultra-wideband (UWB) sensor. It is concluded that when the vital sign is sufficiently strong and pure, all methods, e.g., MPM, VMD, and BPF, are appropriate for vital sign monitoring. However, in noisy cases, MPM has better performance. Therefore, for non-contact microwave vital sign monitoring, which is usually subject to noisy situations, MPM is a powerful method

MNP-enhanced microwave medical imaging by means of pseudo-noise sensing

Magnetic nanoparticles have been investigated for microwave imaging over the last decade. The use of functionalized magnetic nanoparticles, which are able to accumulate selectively within tumorous tissue, can increase the diagnostic reliability. This paper deals with the detecting and imaging of magnetic nanoparticles by means of ultra-wideband microwave sensing via pseudo-noise technology. The investigations were based on phantom measurements. In the first experiment, we analyzed the detectability of magnetic nanoparticles depending on the magnetic field intensity of the polarizing magnetic field, as well as the viscosity of the target and the surrounding medium in which the particles were embedded, respectively. The results show a nonlinear behavior of the magnetic nanoparticle response depending on the magnetic field intensity for magnetic nanoparticles diluted in distilled water and for magnetic nanoparticles embedded in a solid medium. Furthermore, the maximum amplitude of the magnetic nanoparticles responses varies for the different surrounding materials of the magnetic nanoparticles. In the second experiment, we investigated the influence of the target position on the three-dimensional imaging of the magnetic nanoparticles in a realistic measurement setup for breast cancer imaging. The results show that the magnetic nanoparticles can be detected successfully. However, the intensity of the particles in the image depends on its position due to the path-dependent attenuation, the inhomogeneous microwave illumination of the breast, and the inhomogeneity of the magnetic field. Regarding the last point, we present an approach to compensate for the inhomogeneity of the magnetic field by computing a position-dependent correction factor based on the measured magnetic field intensity and the magnetic susceptibility of the magnetic particles. Moreover, the results indicate an influence of the polarizing magnetic field on the measured ultra-wideband signals even without magnetic nanoparticles. Such a disturbing influence of the polarizing magnetic field on the measurements should be reduced for a robust magnetic nanoparticles detection. Therefore, we analyzed the two-state (ON/OFF) and the sinusoidal modulation of the external magnetic field concerning the detectability of the magnetic nanoparticles with respect to these spurious effects, as well as their practical application

Objektorientierte Programmierung von Methoden der zeitvarianten Bispektralanalyse in der Biosignalverarbeitung

Die Notwendigkeit des Einsatzes zeitvarianter Methoden in der Bispektralanalyse liegt im zumeist nichtstationären Charakter biologischer Signale begründet, wodurch die Anwendung klassischer, intervallbezogener Verfahren nur begrenzt möglich ist. Die trifft besonders auf transient auftretende quadratische Phasenkopplungen zu. Eine neue Methode auf der Basis der adaptiv rekursiven Schätzung der Kumulanten III. Ordnung wurde entwickelt und in [1] vorgestellt. Bei der Entwicklung moderner Verfahren der Biosignalverarbeitung rückt neben der Bedeutung der signalanalytischen Merkmale die Effizienz ihrer Implementierung immer mehr in den Vordergrund. In der vorliegenden Arbeit wird die Umsetzung mit Hilfe objektorientierter Programmierung vorgestellt

Preliminary investigations of magnetic modulated nanoparticles for microwave breast cancer detection

This paper investigates the potential of magnetic modulated iron oxide nanoparticles in terms of a contrast enhancement for Ultra-wideband (UWB) breast imaging. The work is motivated by the low dielectric contrast between tumor and normal glandular/fibroconnective tissue. The influence of an external polarizing magnetic field on pure and coated magnetite nanoparticles is investigated in this contribution. Measurements were conducted using M-sequence UWB technology and an oil-gelatin phantom. It is shown that a coating, which is necessary for clinical use, results in a lower signal response, and thus leads to a lower detectability of magnetic modulated nanoparticles

Rekursive Wigner-Spektralanalyse höherer Ordnung

An appropriate spectral analysis of nonstationary signals requires time-variant methods. Going out from the approach of time-variant spectral and bispectral analysis based on the adaptively recursively estimated 2nd and 3rd order cumulants, an optimised algorithm is presented. It can be generalised as special kind of smoothed Pseudo-Wigner-Distribution. The benefit is the recursive calculation of its kernel . Therefore, the method is convementfor higher-order spectral analysis of ongoing signals

Hardware dependencies of GPU-accelerated beamformer performances for microwave breast cancer detection

UWB microwave imaging has proven to be a promising technique for early-stage breast cancer detection. The extensive image reconstruction time can be accelerated by parallelizing the execution of the underlying beamforming algorithms. However, the efficiency of the parallelization will most likely depend on the grade of parallelism of the imaging algorithm and of the utilized hardware. This paper investigates the dependencies of two different beamforming algorithms on multiple hardware specification of several graphics boards. The parallel implementation is realized by using NVIDIA’s CUDA. Three conclusions are drawn about the behavior of the parallel implementation and how to efficiently use the accessible hardware

Zeitvariante Bispektralanalyse auf der Basis einer adaptiv rekursiven Fouriertransformation

An appropriate investigation of quadratic phuw conplings (QPC) in non-stationary Signals requires (inie-\'iiruint methods ofbispectral anulysis. A wir approach for tiine-variant estimation of power spcctrntn and bispectnun bascd on an adaptively, recnr-.vnv/v estimated Fourier transfonn (ADFT) is presenied in this paper. A rednced calculation effort and the possibility of the calculation of the bispectnun for selected frequency triples are important advantages of this method. Becaitse of the recursive calculation, the ADFT is convenient for analysing ongoing Signals. This will he demonstrated for sinmlated and real biomedical Signals