Mariuca-Roxana Gavriloaia

Chirp signal analysis with amplitude modulation

Signals with linear frequency modulation are used in synthetic aperture radar to improve spatial resolution and signal/noise ratio. Acoustic field is proposed in this paper to investigate objects, because it could penetrate them, and propagate inside. When input signal frequency is about resonance frequency, the attenuation is increased, and as a result, the scattered acoustic field is decreased as well. So, a linear frequency modulation signal with constant amplitude is sent to the investigated object, and variable amplitude is reflected, corresponding to the object resonance frequencies. A new method for detection the amplitude modulation of these signals in presence of noise is presented. The method uses the fractional Fourier transform in two steps. In the first step a rotation of signal by the angle=450 is done. The all spectral components outside central band are canceled. After that a new rotation of new function with the same angle is done. The simulated results are presented. The method gives good results of amplitude modulation detection for signals with complex modulation signals having signal - noise ratio in power up to - 5 dB. By knowing the resonance frequencies it is possible to specify the largest 3D object dimension, appreciate the relative values of the other dimensions, and do a rough classification of that object. The presented method could be used for rough classification of buried objects in earth or to early diagnose whether a tumor tissue is or not malignant.

Spatiotemporal filtering for medical images from an infrared camera

In this paper we proposed an improved method for images filtering with slow time variation obtained from some successive frames of a thermovision camera investigating the heat radiated by human beings. In the first step, a single image is obtained as a result of the mean value evaluation from median filtering of all temporal frames. The standard deviation of each pixel is computed as well. The second stage consisted of a spatial filtering of the image from the first step by using the anisotropic diffusion filtering. New relations for the weighted coefficients of the diffusion matrix were proposed from the local statistic estimators. This method was tested on infrared images of different patients. Both subjective and objective evaluations of a patient image suffering from papillary thyroid cancer showed good performances for improving the signal to noise ratio and location of tumor.

An improved method for IR image filtering

One of the most widely used denoising techniques with well preserving edge features in medical imaging is anisotropic diffusion filtering. It is based on the iterative solving of the diffusion equation that takes into account only the heat propagation by conduction1. At living beings, blood perfusion represents another important way to transfer the heat. In this case, we used a new equation modeling the heat propagation, mainly Pennes equation2, processing both conductive and convective heat components. Unlike heat, white noise, which accompanies the signal detected by a thermal sensor, is not a solution to this equation. The new filtering method consists in an iterative solving of bio-heat equation by using Crank-Nicolson convergent algorithm. Bazan’s criterion for stopping iterations agrees well with the behavior of this filter. The filter was tested on some theoretical models of images simulating different signals and noises, and on many thermal images of healthy people or patients suffering from different types of thyroid disorders. One image processing of a patient suffering from papillary carcinoma is shown at different time moments. The noise is rapid attenuated, and it is possible to assess the contour shape or to locate more outbreaks in a certain area, if any.

Bioacoustics response of small benign or malignant nodules

One of the most important features of separation between benign or malignant tissues is their smooth or rough shape. This article presents a new method for early diagnosis of thyroid cancer by knowing the resonance frequencies of a certain tissue. Two types of nodules were investigated: spherical and elliptical. Their external surfaces were smooth or rough with different values of spicules. Propagation of sound through the human body was modeled by a classical partial differential equation associated with Neumann or Dirichlet boundary conditions. The assessments of about ten acoustic eigenfrequencies are enough to decide the type of external surfaces: smooth or rough, or whether nodule is benign or malignant. Data obtained by this method refers to the result of investigating 3D bodies smaller than 5 mm, when other medical devices such as ultrasound or CT cannot evaluate their surface shape because of their limited spatial resolution.

The influence of a malignant nodule on resonance frequencies of the thyroid gland

The thyroid is investigated as a resonant cavity. A number of 16 eigenfrequencies and eigenmodes are evaluated for a thyroid geometric model excited by ultrasounds. The malignant tissue was modelled by spheres with different diameters. The spatial distributions of the acoustic eigenmodes are in accordance with blood supplier positions. Blood supplier efficiency and local temperature will decrease as a result of nodules or cysts. The acoustic field eigenfrequency for the same propagation mode is bigger when thyroid has a malignant nodule. Efficiency of ultrasound diagnosis and thyroid treatment will be increased by knowing these modes and frequencies.

Using fractal analysis of thermal signatures for thyroid disease evaluation

The skin is the largest organ of the body and it protects against heat, light, injury and infection. Skin temperature is an important parameter for diagnosing diseases. Thermal analysis is non-invasive, painless, and relatively inexpensive, showing a great potential research. Since the thyroid regulates metabolic rate it is intimately connected to body temperature, more than, any modification of its function generates a specific thermal image on the neck skin. The shapes of thermal signatures are often irregular in size and shape. Euclidean geometry is not able to evaluate their shape for different thyroid diseases, and fractal geometry is used in this paper. Different thyroid diseases generate different shapes, and their complexity are evaluated by specific mathematical approaches, fractal analysis, in order to the evaluate selfsimilarity and lacunarity. Two kinds of thyroid diseases, hyperthyroidism and papillary cancer are analyzed in this paper. The results are encouraging and show the ability to continue research for thermal signature to be used in early diagnosis of thyroid diseases.

Thermal effect of microwave antenna radiation on a generic model of thyroid gland

The rapid diffusion of wireless communication systems has caused an increased concern for the potential detrimental effects on human health deriving from exposure to electromagnetic field. It penetrates the body and acts on all the organs, altering the cell membrane potential and the distribution of ions and dipoles. The thyroid gland is one of the most exposed vital organs and may be a target for electromagnetic radiation. This paper presents the computed temperature and specific absorption rate inside to a generic model of a human thyroid using signals radiated by an antenna operating in the 2450 MHz band and the power density levels up to 100 W/cm2. Calculations were carried out using the Finite Difference Time Domain method for the solving of two coupled differential equations, Maxwell and Pennes. The results show that the temperature can rise up to very dangerous levels, i.e., 46 °C, in a very short time. The estimated temperature distribution in the human thyroid due to exposure from microwave signals can be used to design the dangerous aria for personal working around high power emitted antenna and for medical applications.

Infrared Signature Analysis of the Thyroid Tumors

Cancer is a leading cause of death worldwide, and about 30% of cancer deaths can be prevented. In the next future, the number of global cancer deaths is projected to increase 45% in the future. A general treatment has not yet been found. The best defense against cancer is early detection, when tumor dimensions are very small. The methods as mammography, ultrasounds, MRI, CT, etc., can detect anatomic or structural changes like tumors and cysts. They are anatomical imaging procedures, consequently, they have the ability to locate the area of the tumor, but they cannot detect a fast-growing cancer in the pre-invasive stage. Thermograms are looking for the physiologic changes in tissue; which may indicate a risk of developing cancer in the future. The results using a new device, operating in infrared band, are described. The paper focuses on thyroid cancer because it allows investigations on larger areas before surgery and on residual, smaller areas following surgery. The experiment results for 24 patients with thyroid nodules are described. Malign tumors have a distinct infrared signature. Only the area affected is thermal registered and that has an irregular shape and a strong nonuniform structure with rapid variations on skin temperature.