Uncertainty analysis of Altantic salmon fish scale's acoustic impedance using 30 MHz C-Scan measurements.

Understanding the biomechanics of fish scales is crucial for their survival and adaptation. Ultrasonic C-scan measurements offer a promising tool for non-invasive characterization, however, existing literature lacks uncertainty analysis while evaluating acoustic impedance. This article presents an innovative integration of uncertainty into the analytical framework for estimating stochastic specific acoustic impedance of salmon fish scale through ultrasonic C-scans. In this study, the various types of uncertainties arising due to variation in biological structures and aging, measurement errors, and analytical noises are combined together in the form of uncertain reflectance. This uncertain reflectance possesses a distribution which is derived using a theory of waves by assuming suitable stochasticity in wavenumber. This distribution helps in development of a stochastic-specific acoustic impedance map of the scales which demonstrates the possible deviations of impedance from mean value depending on uncertainties. Furthermore, maximal overlap discrete wavelet transform is employed for efficient time-frequency deconvolution and Kriging for spatial data interpolation to enhance the robustness of the impedance map, especially in scenarios with limited data. The framework is validated by accurately estimating the specific acoustic impedance of well-known materials like a pair of target medium (polyvinylidene fluoride) and reference medium (polyimide), achieving over 90% accuracy. Moreover, the accuracy of the framework is found superior when compared with an established approach in the literature. Applying the framework to salmon fish scales, we obtain an average specific acoustic impedance of 3.1 MRayl along with a stochastic map visualizing the potential variations arising from uncertainties. Overall, this work paves the way for more accurate and robust studies in fish scale biomechanics by incorporating a comprehensive uncertainty analysis framework.

Automated tilt compensation in acoustic microscopy.

Scanning acoustic microscopy (SAM) is a potent and nondestructive technique capable of producing three-dimensional topographic and tomographic images of specimens. This is achieved by measuring the differences in time of flight (ToF) of acoustic signals emitted from various regions of the sample. The measurement accuracy of SAM strongly depends on the ToF measurement, which is affected by tilt in either the scanning stage or the sample stage. Hence, compensating for the ToF shift resulting from sample tilt is imperative for obtaining precise topographic and tomographic profiles of the samples in a SAM. In the present work, we propose an automated tilt compensation in ToF of acoustic signal based on proposed curve fitting method. Unlike the conventional method, the proposed approach does not demand manually choosing three separate coordinate points from SAM's time domain data. The effectiveness of the proposed curve fitting method is demonstrated by compensating time shifts in ToF data of a coin due to the presence of tilt. The method is implemented for the correction of different amounts of tilt in the coin corresponding to angles 6.67°, 12.65° and 15.95°. It is observed that the present method can perform time offset correction in the time domain data of SAM with an accuracy of 45 arcsec. The experimental results confirm the effectiveness of the suggested tilt compensation technique in SAM, indicating its potential for future applications.

Image denoising in acoustic microscopy using block-matching and 4D filter.

Scanning acoustic microscopy (SAM) is a label-free imaging technique used in biomedical imaging, non-destructive testing, and material research to visualize surface and sub-surface structures. In ultrasonic imaging, noises in images can reduce contrast, edge and texture details, and resolution, negatively impacting post-processing algorithms. To reduce the noises in the scanned image, we have employed a 4D block-matching (BM4D) filter that can be used to denoise acoustic volumetric signals. BM4D filter utilizes the transform domain filtering technique with hard thresholding and Wiener filtering stages. The proposed algorithm produces the most suitable denoised output compared to other conventional filtering methods (Gaussian filter, median filter, and Wiener filter) when applied to noisy images. The output from the BM4D-filtered images was compared to the noise level with different conventional filters. Filtered images were qualitatively analyzed using metrics such as structural similarity index matrix (SSIM) and peak signal-to-noise ratio (PSNR). The combined qualitative and quantitative analysis demonstrates that the BM4D technique is the most suitable method for denoising acoustic imaging from the SAM. The proposed block matching filter opens a new avenue in the field of acoustic or photoacoustic image denoising, particularly in scenarios with poor signal-to-noise ratios.

Stiffness tensor estimation of anisotropic crystal using point contact method and unscented Kalman filter.

The potential application of Lithium Niobate (LiNbO3) crystal is immense, specifically in the domain of meta-surfaces and nano-resonators. However, the practical application of LiNbO3 is impeded due to unreliable experimental techniques and inaccurate inversion algorithms for material characterization. In the current research, material characterization of anisotropic crystal is proposed by exploring the wavefield evolution in the spatial and temporal domains. The presented framework has three major components: a physics-based mathematical model (Christoffel equation), a novel experimental technique, and an inversion algorithm based on Bayesian filtering. An experimental technique based on Coulomb coupling is devised to visualize the propagation of ultrasonic waves in an anisotropic crystal. The crystal is characterized by measuring the directional-dependent acoustic wave velocity from the spatial-temporal information of the wave propagation. The anisotropic constitutive properties of the crystal are estimated by exploring the wave velocity in the Bayesian filtering algorithm. The proposed algorithm is based on the probabilistic framework that integrates the experimental measurement in a physics-based mathematical model for optimal state prediction of stiffness tensor through the Bayesian filtering algorithm. In particular, we utilize the unscented Kalman filter (UKF) in conjunction with the plane-wave Eigen solution to estimate the constitutive parameters. In the presence of measurement uncertainties, the performance of the optimal prediction algorithm is illustrated by comparing the estimated parameter with the corresponding theoretical value. The comparison demonstrates that the proposed inversion algorithm is efficient and robust and performs satisfactorily even with significant measurement uncertainties.

Ultrasonic image denoising using machine learning in point contact excitation and detection method.

A point contact/Coulomb coupling technique is generally used for visualizing the ultrasonic waves in Lead Zirconate Titanate (PZT) ceramics. The point contact and delta pulse excitation produce a broadband frequency spectrum and wide directional wave vector. In ultrasonic, the signal is corrupted with several types of noises such as speckle, Gaussian, Poisson, and salt and pepper noise. Consequently, the resolution and quality of the images are degraded. The reliability of the health assessment of any civil or mechanical structures highly depends on the ultrasonic signals acquired from the sensors. Recently, deep learning (DL) has been implemented for the reduction of noises from the signals and in images. Here, we have implemented deep learning-based convolutional autoencoders for suitable noise modeling and subsequently denoising the ultrasonic images. Two different metrics, PSNR and SSIM are calculated for quantitative analysis of ultrasonic images. PSNR provides higher visual interpretation, whereas the SSIM can be used to measure much finer similarities. Based upon these parameters speckle-noise demonstrated better than other noise models.

Multiple Damage Detection in PZT Sensor Using Dual Point Contact Method.

Lead Zirconate Titanate (PZT) is used to make ultrasound transducers, sensors, and actuators due to its large piezoelectric coefficient. Several micro-defects develop in the PZT sensor due to delamination, corrosion, huge temperature fluctuation, etc., causing a decline in its performance. It is thus necessary to identify, locate, and quantify the defects. Non-Destructive Structural Health Monitoring (SHM) is the most optimal and economical evaluation method. Traditional ultrasound SHM techniques have a huge impedance mismatch between air and solid material, and most of the popular signal processing methods define time series signals in only one domain, which provides sub-optimal results for non-stationary signals. Thus, to improve the accuracy of detection, the point contact excitation and detection method is implemented to determine the interaction of ultrasonic waves with micro-scale defects in the PZT. The signal generated from this method being non-stationary in nature, it requires signal processing with changeable resolutions at different times and frequencies. The Haar Discrete Wavelet Transformation (DWT) is applied to the time series data obtained from the coulomb coupling setup. Using the above process, defects up to 100 µm in diameter could be successfully distinguished.

High-throughput spatial sensitive quantitative phase microscopy using low spatial and high temporal coherent illumination.

High space-bandwidth product with high spatial phase sensitivity is indispensable for a single-shot quantitative phase microscopy (QPM) system. It opens avenue for widespread applications of QPM in the field of biomedical imaging. Temporally low coherence light sources are implemented to achieve high spatial phase sensitivity in QPM at the cost of either reduced temporal resolution or smaller field of view (FOV). In addition, such light sources have low photon degeneracy. On the contrary, high temporal coherence light sources like lasers are capable of exploiting the full FOV of the QPM systems at the expense of less spatial phase sensitivity. In the present work, we demonstrated that use of narrowband partially spatially coherent light source also called pseudo-thermal light source (PTLS) in QPM overcomes the limitations of conventional light sources. The performance of PTLS is compared with conventional light sources in terms of space bandwidth product, phase sensitivity and optical imaging quality. The capabilities of PTLS are demonstrated on both amplitude (USAF resolution chart) and phase (thin optical waveguide, height ~ 8 nm) objects. The spatial phase sensitivity of QPM using PTLS is measured to be equivalent to that for white light source and supports the FOV (18 times more) equivalent to that of laser light source. The high-speed capabilities of PTLS based QPM is demonstrated by imaging live sperm cells that is limited by the camera speed and large FOV is demonstrated by imaging histopathology human placenta tissue samples. Minimal invasive, high-throughput, spatially sensitive and single-shot QPM based on PTLS will enable wider penetration of QPM in life sciences and clinical applications.

High-Frequency Acoustic Imaging Using Adhesive-Free Polymer Transducer.

The piezoelectric polymer PVDF and its copolymers have a long history as transducer materials for medical and biological applications. An efficient use of these polymers can potentially both lower the production cost and offer an environment-friendly alternative for medical transducers which today is dominated by piezoelectric ceramics containing lead. The main goal of the current work has been to compare the image quality of a low-cost in-house transducers made from the copolymer P(VDF-TrFE) to a commercial PVDF transducer. Several test objects were explored with the transducers used in a scanning acoustic microscope, including a human articular cartilage sample, a coin surface, and an etched metal film with fine line structures. To evaluate the image quality, C- and B-scan images were obtained from the recorded time series, and compared in terms of resolution, SNR, point-spread function, and depth imaging capability. The investigation is believed to provide useful information about both the strengths and limitations of low-cost polymer transducers.

High spatially sensitive quantitative phase imaging assisted with deep neural network for classification of human spermatozoa under stressed condition.

Sperm cell motility and morphology observed under the bright field microscopy are the only criteria for selecting a particular sperm cell during Intracytoplasmic Sperm Injection (ICSI) procedure of Assisted Reproductive Technology (ART). Several factors such as oxidative stress, cryopreservation, heat, smoking and alcohol consumption, are negatively associated with the quality of sperm cell and fertilization potential due to the changing of subcellular structures and functions which are overlooked. However, bright field imaging contrast is insufficient to distinguish tiniest morphological cell features that might influence the fertilizing ability of sperm cell. We developed a partially spatially coherent digital holographic microscope (PSC-DHM) for quantitative phase imaging (QPI) in order to distinguish normal sperm cells from sperm cells under different stress conditions such as cryopreservation, exposure to hydrogen peroxide and ethanol. Phase maps of total 10,163 sperm cells (2,400 control cells, 2,750 spermatozoa after cryopreservation, 2,515 and 2,498 cells under hydrogen peroxide and ethanol respectively) are reconstructed using the data acquired from the PSC-DHM system. Total of seven feedforward deep neural networks (DNN) are employed for the classification of the phase maps for normal and stress affected sperm cells. When validated against the test dataset, the DNN provided an average sensitivity, specificity and accuracy of 85.5%, 94.7% and 85.6%, respectively. The current QPI + DNN framework is applicable for further improving ICSI procedure and the diagnostic efficiency for the classification of semen quality in regard to their fertilization potential and other biomedical applications in general.

Single-Input and Multiple-Output Surface Acoustic Wave Sensing for Damage Quantification in Piezoelectric Sensors.

The main aim of the paper is damage detection at the microscale in the anisotropic piezoelectric sensors using surface acoustic waves (SAWs). A novel technique based on the single input and multiple output of Rayleigh waves is proposed to detect the microscale cracks/flaws in the sensor. A convex-shaped interdigital transducer is fabricated for excitation of divergent SAWs in the sensor. An angularly shaped interdigital transducer (IDT) is fabricated at 0 degrees and ±20 degrees for sensing the convex shape evolution of SAWs. A precalibrated damage was introduced in the piezoelectric sensor material using a micro-indenter in the direction perpendicular to the pointing direction of the SAW. Damage detection algorithms based on empirical mode decomposition (EMD) and principal component analysis (PCA) are implemented to quantify the evolution of damage in piezoelectric sensor material. The evolution of the damage was quantified using a proposed condition indicator (CI) based on normalized Euclidean norm of the change in principal angles, corresponding to pristine and damaged states. The CI indicator provides a robust and accurate metric for detection and quantification of damage.

Numerical and Experimental Evaluation of High-Frequency Unfocused Polymer Transducer Arrays.

High-frequency unfocused polymer array transducers are developed using an adhesive-free layer-by-layer assembly method. The current paper focuses on experimental and numerical methods for measuring the acoustic performance of these types of array transducers. Two different types of numerical approaches were used to simulate the transducer performance, including a finite element method (FEM) study of the transducer response done in COMSOL 5.2a Multiphysics, and modeling of the excited ultrasonic pressure fields using the open source software k-Wave 1.2.1. The experimental characterization also involves two methods (narrow and broadband pulses), which are measurements of the acoustic reflections picked up by the transducer elements. Later on, measurements were undertaken of the ultrasonic pressure fields in a water-scanning tank using a hydrophone system. Ultrasonic pressure field measurements were visualized at various distances from the transducer surface and compared with the numerical findings.

Scanning Acoustic Microscopy-A Novel Noninvasive Method to Determine Tumor Interstitial Fluid Pressure in a Xenograft Tumor Model.

Elevated tumor interstitial fluid pressure (TIFP) is a prominent feature of solid tumors and hampers the transmigration of therapeutic macromolecules, for example, large monoclonal antibodies, from tumor-supplying vessels into the tumor interstitium. TIFP values of up to 40 mm Hg have been measured in experimental solid tumors using two conventional invasive techniques: the wick-in-needle and the micropuncture technique. We propose a novel noninvasive method of determining TIFP via ultrasonic investigation with scanning acoustic microscopy at 30-MHz frequency. In our experimental setup, we observed for the impedance fluctuations in the outer tumor hull of A431-vulva carcinoma-derived tumor xenograft mice. The gain dependence of signal strength was quantified, and the relaxation of tissue was calibrated with simultaneous hydrostatic pressure measurements. Signal patterns from the acoustical images were translated into TIFP curves, and a putative saturation effect was found for tumor pressures larger than 3 mm Hg. This is the first noninvasive approach to determine TIFP values in tumors. This technique can provide a potentially promising noninvasive assessment of TIFP and, therefore, can be used to determine the TIFP before treatment approach as well to measure therapeutic efficacy highlighted by lowered TFP values.