Microstructural evaluation with type i hot corrosion degradation of gas turbine alloys during burner-rig testing

The hot corrosion resistance of selected gas turbine alloys was evaluated, as a baseline for assessing candidate new hot-section materials. The alloys were tested under burner rig exposures, using ASTM standard seawater for the salt contaminant and combustion conditions that provide representative materials evolution and degradation behavior relative to what is observed with marine gas turbines under service environments. Modern characterization techniques were utilized to evaluate the hot corrosion behavior and resistance of the evaluated material systems, to observe the degradation of the alloys and to study the underlying degradation mechanisms active during hot corrosion attack. Please click Additional Files below to see the full abstract

Global Ultrasound Elastography Using Convolutional Neural Network

Displacement estimation is very important in ultrasound elastography and failing to estimate displacement correctly results in failure in generating strain images. As conventional ultrasound elastography techniques suffer from decorrelation noise, they are prone to fail in estimating displacement between echo signals obtained during tissue distortions. This study proposes a novel elastography technique which addresses the decorrelation in estimating displacement field. We call our method GLUENet (GLobal Ultrasound Elastography Network) which uses deep Convolutional Neural Network (CNN) to get a coarse time-delay estimation between two ultrasound images. This displacement is later used for formulating a nonlinear cost function which incorporates similarity of RF data intensity and prior information of estimated displacement. By optimizing this cost function, we calculate the finer displacement by exploiting all the information of all the samples of RF data simultaneously. The Contrast to Noise Ratio (CNR) and Signal to Noise Ratio (SNR) of the strain images from our technique is very much close to that of strain images from GLUE. While most elastography algorithms are sensitive to parameter tuning, our robust algorithm is substantially less sensitive to parameter tuning.Comment: 4 pages, 4 figures; added acknowledgment section, submission type late

3D Ultrafast Shear Wave Absolute Vibro-Elastography using a Matrix Array Transducer

3D ultrasound imaging provides more spatial information compared to conventional 2D frames by considering the volumes of data. One of the main bottlenecks of 3D imaging is the long data acquisition time which reduces practicality and can introduce artifacts from unwanted patient or sonographer motion. This paper introduces the first shear wave absolute vibro-elastography (S-WAVE) method with real-time volumetric acquisition using a matrix array transducer. In SWAVE, an external vibration source generates mechanical vibrations inside the tissue. The tissue motion is then estimated and used in solving a wave equation inverse problem to provide the tissue elasticity. A matrix array transducer is used with a Verasonics ultrasound machine and frame rate of 2000 volumes/s to acquire 100 radio frequency (RF) volumes in 0.05 s. Using plane wave (PW) and compounded diverging wave (CDW) imaging methods, we estimate axial, lateral and elevational displacements over 3D volumes. The curl of the displacements is used with local frequency estimation to estimate elasticity in the acquired volumes. Ultrafast acquisition extends substantially the possible S-WAVE excitation frequency range, now up to 800 Hz, enabling new tissue modeling and characterization. The method was validated on three homogeneous liver fibrosis phantoms and on four different inclusions within a heterogeneous phantom. The homogeneous phantom results show less than 8% (PW) and 5% (CDW) difference between the manufacturer values and the corresponding estimated values over a frequency range of 80 Hz to 800 Hz. The estimated elasticity values for the heterogeneous phantom at 400 Hz excitation frequency show average errors of 9% (PW) and 6% (CDW) compared to the provided average values by MRE. Furthermore, both imaging methods were able to detect the inclusions within the elasticity volumes

Real-time imaging of elastic properties of soft tissue with ultrasound

Current imaging devices such as computed tomography (CT) , ultrasound (US) and magnetic resonance imaging (MRI) are not directly capable of measuring the mechanical properties of soft tissue even though such measurement would have a high clinical demand. Elastography with the aid of ultrasound has been well established in the literature as a strain imaging technique. Under certain conditions, these strain images can give a clear illustration of the underlying tissue stiffness distributions which has been shown to provide useful clinical information. Vibro Elastography is another new imaging system that performs a transfer function analysis of the tissue motion. The shape of the transfer function can be analyzed further and the stiffness of tissue can be estimated from the magnitude of the transfer functions at low-frequencies. This thesis introduces a fast and accurate motion tracking algorithm which is at the heart of both strain imaging and stiffness imaging. The algorithm achieves real-time performance (> 20 fps) without any need for additional hardware and its overhead. The performance of the proposed method is evaluated quantitatively according to its signal-to-noise ratio, contrast-to-noise ratio, dynamic range, resolution and sensitivity with both simulation data and phantom data. Also, the computational efficiency of the algorithm is compared with current real-time motion tracking algorithms. The results show that it is the most time efficient algorithm to date. Furthermore the performance of the proposed method is evaluated qualitatively from the real-time images that are generated in both tissue mimicking phantoms and real tissues in vivo. By using this method two real-time elastography packages have been implemented which can easily be clinically applied. These implementations run at 35fps for strain images and 2fps for transfer function images of 16,000 pixels on an Ultrasonix RP500 ultrasound machine.Applied Science, Faculty ofElectrical and Computer Engineering, Department ofGraduat

Methods for the estimation of the tissue motion using digitized ultrasound echo signals

Tissue motion estimation in ultrasound images plays a central role in many modern signal processing applications, including tissue characterization, strain and velocity imaging, and tissue viscoelasticity imaging. Therefore, the performance of tissue motion estimation is of significant importance. Also, its computational cost determines if it can be implemented in real-time so that it can be used clinically. This thesis presents several efficient methods for accurate estimation of tissue motion using digitized ultrasound echo signals. First, sample tracking algorithms are presented as a new class of motion estimators. These algorithms are based on the tracking of individual samples using a continuous representation of the reference echo signal. Simulations and experimental results on tissue mimicking phantoms show that sample tracking algorithms significantly outperform common algorithms in terms of accuracy, precision, sensitivity, and resolution. However, their performance degrades in the presence of noise. To improve the performance of motion estimation in multi-dimensions, pattern matching interpolation techniques are studied and new interpolation techniques are presented. Simulation and experimental results show that, with small computational overhead, the proposed interpolation techniques significantly improve the accuracy and the precision of motion estimation in both 2D and 3D. Employing these techniques, real-time 2D motion tracking software is developed. Furthermore, the performance of the proposed 2D estimators is compared with that of 2D tracking using angular compounding. The results show that the proposed interpolation methods bring the performance of pattern matching techniques close to that of 2D compound tracking. Finally, angular compounding is combined with custom pulse sequencing and delay cancellation techniques to develop a system that estimates the motion vectors at very high frame rates (> 500 Hz) in real-time. The application of the system in the study of the propagation of mechanical waves for tissue characterization is also presented.Applied Science, Faculty ofElectrical and Computer Engineering, Department ofGraduat

Modeling of Needle-Tissue Interaction Using Ultrasound-Based Motion Estimation

Abstract. A needle-tissue interaction model is an essential part of every needle insertion simulator. In this paper, a new experimental method for the modeling of needle-tissue interaction is presented. The method consists of measuring needle and tissue displacements with ultrasound, measuring needle base forces, and using a deformation simulation model to identify the parameters of a needle-tissue interaction model. The feasibility of this non-invasive approach was demonstrated in an experiment in which a brachytherapy needle was inserted into a prostate phantom. Ultrasound radio-frequency data and the time-domain cross-correlation method, often used in ultrasound elastography, were used to generate the tissue displacement field during needle insertion. A three-parameter force density model was assumed for the needle-tissue interaction. With the needle displacement, tissue displacement and needle base forces as input data, finite element simulations were carried out to adjust the model parameters to achieve a good fit between simulated and measured data.