Blood Velocities Estimation using Ultrasound

This thesis consists of two parts. In the rst part, the iterative data-adaptive BIAA spectral estimation technique was extended to estimate lateral blood velocities using ultrasound scanners. The BIAA method makes no assumption on samples depth or sampling pattern, and therefore allows for transmission in duplex mode imaging. The technique was examined on a realistic Field II simulation data set, and showed fewer spectral artifacts in comparison with other techniques. In the second part of the thesis, another common problem in blood velocity estimation has been investigated, namely strong backscattered signals from stationary echoes. Two methods have been tested to examine the possibility of overcoming this problem. However, neither of these methods resulted in a better estimation of the blood velocities, most likely as the clutter characteristics in color ow images vary too rapidly to allow for this form of models. This might be a result of the non-stationary tissue motions which could be caused by a variety of factors, such as cardiac activities, respiration, transducer/patient movement, or a combination of them

Fractal Dimension Analysis for Robust Ultrasonic Non-Destructive Evaluation (NDE) of Coarse Grained Materials

Over the recent decades, there has been a growing demand on reliable and robust non-destructive evaluation (NDE) of structures and components made from coarse grained materials such as alloys, stainless steels, carbon-reinforced composites and concrete; however, when inspected using ultrasound, the flaw echoes are usually contaminated by high-level, time-invariant, and correlated grain noise originating from the microstructure and grain boundaries, leading to pretty low signal-to-noise ratio (SNR) and the flaw information being obscured or completely hidden by the grain noise. In this paper, the fractal dimension analysis of the A-scan echoes is investigated as a measure of complexity of the time series to distinguish the echoes originating from the real defects and the grain noise, and then the normalized fractal dimension coefficients are applied to the amplitudes as the weighting factor to enhance the SNR and defect detection. Experiments on industrial samples of the mild steel and the stainless steel are conducted and the results confirm the great benefits of the method

New analysis and extensions of split-spectrum processing algorithms

[EN] In this paper we compare the performances of different variants of split-spectrum algorithms and propose some new extensions based on the use of variable bandwidth filters equally spaced in frequency and energy gain equalized. Signal-to-Noise Ratio Gain and Flaw-to-Clutter Ratio Gain factors were selected as the figures of merit to make the comparisons among the different methods. We considered simulated ultrasonic signals using both stationary and non-stationary models for the grain noise, and real scans obtained in laboratory from low dispersive (aluminum) and high dispersive (cement) materials. Frequency Multiplication (FM) recombination method is revealed as the best option when combined with the new extensions.This work has been supported by the Ministerio de Fomento (Spain) and the Ministerio de Ciencia e Innovacion (Spain), and FEDER funds under the projects T39/2006, TEC2008-06728 and TEC2008-02975Rodríguez, A.; Miralles Ricós, R.; Bosch Roig, I.; Vergara Domínguez, L. (2012). New analysis and extensions of split-spectrum processing algorithms. NDT & E International. 45(1):141-147. https://doi.org/10.1016/j.ndteint.2011.10.001S14114745

Biologically inspired processing of radar and sonar target echoes

Modern radar and sonar systems rely on active sensing to accomplish a variety of tasks, including detection and classification of targets, accurate localization and tracking, autonomous navigation and collision avoidance. Bats have relied on active sensing for over 50 million years and their echolocation system provides remarkable perceptual and navigational performance that are of envy to synthetic systems. The aim of this study is to investigate the mechanisms bats use to process echo acoustic signals and investigate if there are lessons that can be learned and ultimately applied to radar systems. The basic principles of the bat auditory system processing are studied and applied to radio frequencies. A baseband derivative of the Spectrogram Correlation and Transformation (SCAT) model of the bat auditory system, called Baseband SCAT (BSCT), has been developed. The BSCT receiver is designed for processing radio-frequency signals and to allow an analytical treatment of the expected performance. Simulations and experiments have been carried out to confirm that the outputs of interest of both models are “equivalent”. The response of the BSCT to two closely spaced targets is studied and it is shown that the problem of measuring the relative distance between two targets is converted to a problem of measuring the range to a single target. Nearly double improvement in the resolution between two close scatterers is achieved with respect to the matched filter. The robustness of the algorithm has been demonstrated through laboratory measurements using ultrasound and radio frequencies (RF). Pairs of spheres, flat plates and vertical rods were used as targets to represent two main reflectors

Sinusoidal frequency estimation with applications to ultrasound

This thesis comprises two parts. The first part deals with single carrier and multiple-carrier based frequency estimation. The second part is concerned with the application of ultrasound using the proposed estimators and introduces a novel efficient implementation of a subspace tracking technique. In the first part, the problem of single frequency estimation is initially examined, and a hybrid single tone estimator is proposed, comprising both coarse and refined estimates. The coarse estimate of the unknown frequency is obtained using the unweighted linear prediction method, and is used to remove the frequency dependence of the signal-to-noise ratio (SNR) threshold. The SNR threshold is then further reduced via a combination of using an aver aging filter and an outlier removal scheme. Finally, a refined frequency estimate is formed using a weighted phase average technique. The hybrid estimator outperforms other recently developed estimators and is found to be independent of the underlying frequency. A second topic considered in the first part of this thesis is multiple-carrier based frequency estimation. Based on this idea, three novel velocity estimators are proposed by exploiting the velocity dependence of the backscattered carriers using synthetic data, all three proposed estimators are found to exhibit the capability of mitigating the poor high velocity performance of the conventional correlation based techniques and thereby provide usable performance beyond the conventional Nyquist velocity limit. To evaluate these methods statistically, the Cramer-Rao lower bound for the velocity estimation is derived. In the second part, the fundamentals of ultrasound are briefly reviewed. An efficient subspace tracking technique is introduced as a way to implement clutter eigenfilters, greatly reducing the computation complexity as compared to conventional eigenfilters which are based on the evaluation of the block singular value decomposition technique. Finally, the hybrid estimator and the multiple-carrier based velocity estimators proposed in the first part of the thesis are examined with realistic radio frequency data, illustrating the usefulness of these methods in solving practical problems