Quantitative ultrasound has been widely used for tissue characterization. In this paper we propose a new approach for tissue compression assessment. The proposed method employs the relation between the tissue scatterers’ local spatial distribution and the resulting frequency power spectrum of the backscattered ultrasonic signal. We show that due to spatial distribution of the scatterers, the power spectrum exhibits characteristic variations. These variations can be extracted using the empirical mode decomposition and analyzed. Validation of our approach is performed by simulations and in-vitro experiments using a tissue sample under compression. The scatterers in the compressed tissue sample approach each other and consequently, the power spectrum of the backscattered signal is modified. We present how to assess this phenomenon with our method. The proposed in this paper approach is general and may provide useful information on tissue scattering properties.
Ultrasonic methods of human body internal structures imaging are being continuously enhanced. New algorithms are created to improve certain output parameters. A synthetic aperture method (SA) is an example which allows to display images at higher frame-rate than in case of conventional beam-forming method. Higher computational complexity is a limitation of SA method and it can prevent from obtaining a desired reconstruction time. This problem can be solved by neglecting a part of data. Obviously it implies a decrease of imaging quality, however a proper data reduction technique would minimize the image degradation. A proposed way of data reduction can be used with synthetic transmit aperture method (STA) and it bases on an assumption that a signal obtained from any pair of transducers is the same, no matter which transducer transmits and which receives. According to this postulate, nearly a half of the data can be ignored without image quality decrease. The presented results of simulations and measurements with use of wire and tissue phantom prove that the proposed data reduction technique reduces the amount of data to be processed by half, while maintaining resolution and allowing only a small decrease of SNR and contrast of resulting images.
Texture of ultrasound images contain information about the properties of examined tissues. The analysis of statistical properties of backscattered ultrasonic echoes has been recently successfully applied to differentiate healthy breast tissue from the benign and malignant lesions. We propose a novel procedure of tissue characterization based on acquiring backscattered echoes from the heated breast. We have proved that the temperature increase inside the breast modifies the intensity, spectrum of the backscattered signals and the probability density function of envelope samples. We discuss the differences in probability density functions in two types of tissue regions, e.g. cysts and the surrounding glandular tissue regions. Independently, Pennes bioheat equation in heterogeneous breast tissue was used to describe the heating process. We applied the finite element method to solve this equation. Results have been compared with the ultrasonic predictions of the temperature distribution. The results confirm the possibility of distinguishing the differences in thermal and acoustical properties of breast cyst and surrounding glandular tissues.