Probe Position Research Articles

Automated self-adjustment of array probe with a robotic ultrasonic test system

Ultrasonic testing of objects with complex geometries often requires the use of a robotic arm to position the probe perpendicular to the local surface. Using immersion makes it possible to test these objects with standard ultrasonic linear array probes. Here, the probe positions and orientations provided by the robot are used for merging the locally acquired image data into a 3D-reconstruction. The quality of this reconstruction is highly dependent on the alignment of the position of the physical probe with the position used in the digital model. For common industrial tools, the tool center point (TCP) is usually acquired using geometric features of the tools. However, for ultrasonic arrays in immersion, there is a water standoff between the probe and the test object, therefore the TCP is in free space in front of the array and cannot be acquired with the common method. To overcome this challenge, we propose a method that allows the robotic ultrasonic system to automatically self-adjust the position and orientation of the ultrasonic probe using a test block made of steel with defined geometric features as a target for referencing. For each of the six degrees of freedom, a scan and adjustment routine are established using the data based on the actual ultrasound characteristics of the probe. Given a coarse pre-definition of the tool position and the known target test block, minimal human interaction is required to supervise the adjustment method, leading to higher quality reconstructions than with manual adjustment.

Real-time four-dimensional scanning transmission electron microscopy through sparse sampling

Abstract Four-dimensional scanning transmission electron microscopy (4-D STEM) is a state-of-theart image acquisition mode used to reveal high and low mass elements at atomic resolution. The acquisition of the electron momenta at each real space probe location allows for various analyses to be performed from a single dataset, including virtual imaging, electric field analysis, as well as analytical or iterative extraction of the object induced phase shift. However, the limiting factor in 4-D STEM is the speed of acquisition which is bottlenecked by the read-out speed of the camera, which must capture a convergent beam electron diffraction (CBED) pattern at each probe position in the scan. Recent developments in sparse sampling and image inpainting (a branch of compressive sensing) for STEM have allowed for real-time recovery of sparsely acquired data from fixed monolithic detectors, Further developments in compressive sensing for 4-D STEM have also demonstrated that acquisition speeds can be increased i.e. live video rate 4D imaging is now possible. In this work, we demonstrate the first practical implementations of compressive 4-D STEM for real-time inference on two different scanning transmission electron microscopes.

Functional Magnetic Neuromuscular Stimulation vs. Routine Physiotherapy in the Critically Ill for Prevention of ICU Acquired Muscle Loss: A Randomised Controlled Trial

Background and Objectives: Muscle loss is a known complication of ICU admission. The aim of the study was to investigate the effect of neuromuscular functional magnetic stimulation (FMS) on quadriceps muscle thickness in critically ill patients. Materials and Methods: Among ICU patients one quadriceps was randomized to FMS (Tesla Stym,Iskra Medical, Ljubljana, Slovenia) stimulation and the other to control care. Quadriceps thickness was measured by ultrasound (US) in transversal and longitudinal planes at enrolment, Days 3–5, and Days 9–12. The trial stopped early following an interim analysis comparing muscle thickness differences between groups using repeated measures ANOVA. Results: Of 18 patients randomized, 2 died before completing the trial. The final analysis reported included 16 patients (female 38%, age 68 ± 10 years, SOFA 10.8 ± 2.7). Three mild skin thermal injuries were noted initially, which were later avoided with proper positioning of FMS probe. Primary outcome comparison showed that quadriceps thickness in transversal and longitudinal planes decreased in the non-stimulated legs and, but it did not change in FMS legs (−4.1 mm (95%CI: −9.4 to −0.6) vs. −0.7 mm (95%CI: −4.1 to −0.7) (p = 0.03) and −4.4 mm (95%CI: −8.9 to −1.1) vs. −1.5 mm (95%CI: −2.6 to −2.2) (p = 0.02), respectively) (ANOVA difference between groups p = 0.036 and 0.01, respectively). Conclusions: In the critically ill, neuromuscular FMS is feasible and safe with precautions applied to avoid possible skin thermal injury. FMS decreases the loss of quadriceps muscle thickness.

Enhancing sensitivity in fluorescence measurements across an ultra-wide concentration range through optimizing combined-segments strategy

Fluorescence measurement technology is crucial in analytical instrumentation. However, when applied in fields such as environmental science and medical research for quantification purposes, it requires prior estimation of sample concentration and sample dilution to ensure measurement precision. This requirement presents challenge for its broader application in online fluorescence sensing. This study addresses the challenge of achieving high-precision measurements across an ultra-wide concentration range, which is critical for applications ranging from environmental monitoring to clinical diagnostics. The binary segmentation method can initially achieve the goal of ultra-wide range fluorescence measurement, but it fails to maintain sensitivity and precision across the entire range, with relative errors exceeding ±15%. Therefore, we propose an optimizing combined-segments strategy, which examines the effects of adjusting the fluorescence reception position, range, and region interval parameters of the fluorescence reception probes on measurement sensitivity limits. This strategy aims to find the optimal measurement sensitivity limit (lmopt) and the best combined-segments configuration based on more than one quantitative relationship curves. Experimental results demonstrate that within a concentration range 20 times broader than the linear range, it can effectively maintain relative errors within ±5%. This enhances the applicability of fluorescence sensing techniques in various practical settings and advances online and direct fluorescence measurement technologies across an ultra-wide concentration range.

Adaptive probe position correction for automated complex weld inspection based on structural signal monitoring

ABSTRACT To ensure comprehensive coverage of welds, multi-axis motions are necessary for the probe during the automatic detection of complex welds. Guaranteeing the effectiveness of ultrasonic data during this process is crucial for ensuring detection accuracy and reliability. Taking tubular Y-joints as an example, this paper presents an adaptive probe posture correction method based on structural signal monitoring: (1) The structural and acoustic model of tubular Y-joints is established to select and predict the target structural signal. (2) Feature extraction and signal tracking algorithms are developed to achieve real-time monitoring of signals. (3) A posture correction method is proposed based on signal characteristics: time-domain characteristics correspond to position adjustments, while amplitudes correspond to orientation corrections. Building upon this, a feedback mechanism for probe posture is established. The effectiveness of the developed method is verified through underwater automatic detection experiments of tubular Y-joints. Results demonstrate that, with the assistance of the probe posture correction method, the coverage of the effective area increases to more than 95%, and embedded defects are fully detected through a single scan. In conclusion, the adaptive probe posture correction method based on structural signal monitoring presents a promising approach for the automatic ultrasonic examination of complex welds.

Unsupervised deep denoising for four-dimensional scanning transmission electron microscopy

By simultaneously achieving high spatial and angular sampling resolution, four dimensional scanning transmission electron microscopy (4D STEM) is enabling analysis techniques that provide great insight into the atomic structure of materials. Applying these techniques to scientifically and technologically significant beam-sensitive materials remains challenging because the low doses needed to minimise beam damage lead to noisy data. We demonstrate an unsupervised deep learning model that leverages the continuity and coupling between the probe position and the electron scattering distribution to denoise 4D STEM data. By restricting the network complexity it can learn the geometric flow present but not the noise. Through experimental and simulated case studies, we demonstrate that denoising as a preprocessing step enables 4D STEM analysis techniques to succeed at lower doses, broadening the range of materials that can be studied using these powerful structure characterization techniques.

Exploration of the Conditions for Occurrence of Photoplethysmographic Signal Inversion above the Dorsalis Pedis Artery.

Inversion of the photoplethysmographic (PPG) signal is a rarely reported case. This signal anomaly can have implications for PPG-based cardiovascular assessments. The conditions for PPG signal inversion in the vicinity of the dorsalis pedis (DPA) artery of the foot were investigated. Wireless multi-wavelength PPG sensing with skin-probe contact pressure and local skin temperature were studied at different sensor positions, and the occurrence of inversion (OOI) was investigated. Twelve healthy adult volunteers were studied over four LED wavelengths at three levels of contact pressure for 11 probe positions. A novel algorithm quantified the proportion of inverted samples with respect to the abovementioned variables. Our algorithm classifying inverted vs. non-inverted pulses achieved 98.3% accuracy. Ten of the participants had at least one inverted signal identified. The impact of interindividual variation on inversion prevalence was large, but different LEDs, relative position to the DPA and sensor contact pressure also affected OOI. Skin surface and room temperatures showed no impact on OOI. Lateral measurements showed 39.6% more inversion at maximum compared to minimum contact pressure. Mechanical capillary bed variations and arterial reflections during venous engorgement are considered viable explanations for our observations. These findings motivate an expanded study of the occurrence of PPG signal inversion.

Advanced Compressive Sensing and Dynamic Sampling for 4D-STEM Imaging of Interfaces.

Interfaces in energy materials and devices often involve beam-sensitive materials such as fast ionic, soft, or liquid phases. 4D scanning transmission electron microscopy (4D-STEM) offers insights into local lattice, strain charge, and field distributions, but faces challenges in analyzing beam-sensitive interfaces at high spatial resolutions. Here, a 4D-STEM compressive sensing algorithm is introduced that significantly reduces data acquisition time and electron dose. This method autonomously allocates probe positions on interfaces and reconstructs missing information from datasets acquired via dynamic sampling. This algorithm allows for the integration of various scanning schemes and electron probe conditions to optimize data integrity. Its data reconstruction employs a neural network and an autoencoder to correlate diffraction pattern features with measured properties, significantly reducing training costs. The accuracy of the reconstructed 4D-STEM datasets is verified using a combination of explicitly and implicitly trained parameters from atomic resolution datasets. This method is broadly applicable for 4D-STEM imaging of any local features of interest and will be available on GitHub upon publication.

Effect of current probe location on response law of shielded multi-core wire

Abstract Bulk current injection (BCI) is a commonly used method in electromagnetic compatibility testing. In order to enhance the injection efficiency of the current probe, the interference process into the internal core wire is analyzed. Theoretical calculations indicate that the shielded multi-core wire exhibits a frequency selective response under BCI conditions. The-peak of the terminal load response voltage occurs at frequencies corresponding to the integral multiples of half the relative length of the cable. The position of the current probe along the cable only affects the amplitude of the distributed current on the shielding layer, but not its distribution pattern. The response of the internal core wire at the resonant frequencies is positively correlated with the distribution pattern of the distributed current on the shielding layer. The probe position has a significant effect on the magnitude of the wire-to-terminal response. Placing the current probe at both ends of the cable results in high injection efficiency and significant power savings.

SNPscan Combined With CNVplex as a High-Performance Diagnostic Method for Thalassemia.

Thalassemia is a Mendelian-inherited blood disorder with severe consequences, including disability and mortality, making it a significant public health concern. Therefore, there is an urgent need for precise diagnostic technologies. We introduce two innovative diagnostic techniques for thalassemia, SNPscan and CNVplex, designed to enhance molecular diagnostics of thalassemia. The SNPscan and CNVplex assays utilize variations in PCR product length and fluorescence to identify multiple mutations. In the SNPscan method, we designed three probes per locus: two 5' and one 3', and incorporated allele identification link sequences into one of the 5' probes to distinguish the alleles. The detection system was designed for 67 previously reported loci in the Chinese population for a specific genetic condition. CNVplex identifies deletion types by analyzing the specific positions of probes within the globin gene. This innovative approach enables the detection of six distinct deletional mutations, enhancing the precision of thalassemia diagnostics. We evaluated and refined the methodologies in a training cohort of 100 individuals with confirmed HBA and HBB genotypes. The validation cohort, consisting of 1647 thalassemia patients and 100 healthy controls, underwent a double-blind study. Traditional diagnostic techniques served as the control methods. In the training set of 100 samples, 10 mutations (Hb QS, Hb CS, Hb Westmead, CD17, CD26, CD41-42, IVS-II-654, --SEA, -α3.7 and -α4.2) were identified, consistent with those identified by traditional methods. The validation study showed that SNPscan/CNVplex offered superior molecular diagnostic capabilities for thalassemia, with 100% accuracy compared to 99.43% for traditional methods. Notably, the assay identified three previously undetected mutations in 10 cases, including two deletion mutations (Chinese Gγ(Aγδβ)0 del and SEA-HPFH), and one non-deletion mutation (Hb Q-Thailand). The SNPscan/CNVplex assay is a cost-effective and user-friendly tool for diagnosing thalassemia, demonstrating high accuracy and reliability, and showing great potential as a primary diagnostic method in clinical practice.

A composite testing method of homologous magnetic flux leakage and motion-induced eddy current for inner and outer defects

Magnetic flux leakage (MFL) testing, widely utilized for pipeline integrity assessments due to its efficiency and accuracy, is often challenged by motion-induced eddy currents (MIEC) that can distort MFL signals. Contrary to traditional perspectives that consider MIEC as detrimental, this paper introduces a novel MFL-MIEC composite testing method. This method leverages MIEC as a complementary technique while sharing the same excitation source. By exploring the generation and influence of MIEC on MFL signals, we simulate optimal probe positions and analyze the effects of defect position, angle, and detection speed on signal quality. Adjustments in the detection coils orientation are shown to enhance signal strength, demonstrating the methods effectiveness in identifying pipeline defects through practical experiments. This approach offers significant potential for widespread application in pipeline assessments.

Small animal brain surgery with neither a brain atlas nor a stereotaxic frame

BackgroundStereotaxic surgery is a cornerstone in brain research for the precise positioning of electrodes and probes, but its application is limited to species with available brain atlases and tailored stereotaxic frames. Addressing this limitation, we introduce an alternative technique for small animal brain surgery that requires neither an aligned brain atlas nor a stereotaxic frame. New methodThe new method requires an ex-vivo high-contrast MRI brain scan of one specimen and access to a micro-CT scanner. The process involves attaching miniature markers to the skull, followed by CT scanning of the head. Subsequently, MRI and CT images are co-registered using standard image processing software and the targets for brain recordings are marked in the MRI image. During surgery, the animal's head is stabilized in any convenient orientation, and the probe’s 3D position and angle are tracked using a multi-camera system. We have developed a software that utilizes the on-skull markers as fiducial points to align the CT/MRI 3D model with the surgical positioning system, and in turn instructs the surgeon how to move the probe to reach the targets within the brain. ResultsOur technique allows the execution of insertion tracks connecting two points in the brain. We successfully applied this method for neuropixels probe positioning in owls, quails, and mice, demonstrating its versatility. Comparison with existing methodsWe present an alternative to traditional stereotaxic brain surgeries that does not require established stereotaxic tools. Thus, this method is especially of advantage for research in non-standard and novel animal models.

Predicting ptychography probe positions using single-shot phase retrieval neural network

Predicting ptychography probe positions using single-shot phase retrieval neural network

Diffusion distribution model for damage mitigation in scanning transmission electron microscopy.

Despite the widespread use of Scanning Transmission Electron Microscopy (STEM) for observing the structure of materials at the atomic scale, a detailed understanding of some relevant electron beam damage mechanisms is limited. Recent reports suggest that certain types of damage can be modelled as a diffusion process and that the accumulation effects of this process must be kept low in order to reduce damage. We therefore develop an explicit mathematical formulation of spatiotemporal diffusion processes in STEM that take into account both instrument and sample parameters. Furthermore, our framework can aid the design of Diffusion Controlled Sampling (DCS) strategies using optimally selected probe positions in STEM, that constrain the cumulative diffusion distribution. Numerical simulations highlight the variability of the cumulative diffusion distribution for different experimental STEM configurations. These analytical and numerical frameworks can subsequently be used for careful design of 2- and 4-dimensional STEM experiments where beam damage isminimised.

Considerations for extracting moiré-level strain from dark field intensities in transmission electron microscopy

Bragg interferometry (BI) is an imaging technique based on four-dimensional scanning transmission electron microscopy (4D-STEM) wherein the intensities of select overlapping Bragg disks are fit or more qualitatively analyzed in the context of simple trigonometric equations to determine local stacking order. In 4D-STEM based approaches, the collection of full diffraction patterns at each real-space position of the scanning probe allows the use of precise virtual apertures much smaller and more variable in shape than those used in conventional dark field imaging such that even buried interfaces marginally twisted from other layers can be targeted. With a coarse-grained form of dark field ptychography, BI uses simple physically derived fitting functions to extract the average structure within the illumination region and is, therefore, viable over large fields of view. BI has shown a particular advantage for selectively investigating the interlayer stacking and associated moiré reconstruction of bilayer interfaces within complex multi-layered structures. This has enabled investigation of reconstruction and substrate effects in bilayers through encapsulating hexagonal boron nitride and of select bilayer interfaces within trilayer stacks. However, the technique can be improved to provide a greater spatial resolution and probe a wider range of twisted structures, for which current limitations on acquisition parameters can lead to large illumination regions and the computationally involved post-processing can fail. Here, we analyze these limitations and the computational processing in greater depth, presenting a few methods for improvement over previous works, discussing potential areas for further expansion, and illustrating the current capabilities of this approach for extracting moiré-scale strain.

Tetrakis(trimethylsilyl)silane as a standard compound for fast spinning Solid-State NMR experiments

The development of magic angle spinning (MAS) at rates ranging from 30 kHz to greater than 100 kHz has substantially advanced solid-state nuclear magnetic resonance (SSNMR) spectroscopy 1H-detection methods. The small rotors required for such MAS rates have a limited sample volume and low 13C-detection sensitivity, rendering the traditional set of standard compounds for SSNMR insufficient or highly inconvenient for shimming and magic-angle calibration. Additionally, the reproducibility of magic angle setting, chemical shift referencing, and probe position can be especially critical for SSNMR experiments at high fields. These conditions suggest the need for a high signal-to-noise ratio (SNR) 1H-detection standard compound, which is preferably multi-purpose, to simplify instrument set up for ultra-fast MAS SSNMR instruments at high magnetic fields. In this study, we present the results for setting magic angle and shimming using tetrakis(trimethylsilyl)silane (TTMSS, or TKS), a tetramethylsilane (TMS) analogue, at near 40 kHz and demonstrate that we can achieve favorable results in less time but with equal or superior precision as traditional KBr and adamantane standards. The high SNR and TMS-like chemical shift of TKS also opens the possibilities for using TKS as an internal standard with biological samples. A single rotor containing a four-component mixture of TKS, adamantane, uniformly 13C, 15N-labeled N-acetyl valine and KBr was used to perform a complete configuration and calibration of a SSNMR probe without sample changes. We anticipate TKS as a standard compound to be especially effective at very high MAS conditions and to greatly simplify the instrument set up for high and ultra-high field SSNMR instruments.

Deep learning for ultrasound surface echo detection

Ultrasound array imaging techniques are often applied using a coupling medium to transmit waves from the transducer to the scanned component. In this type of tests, the echoes generated by the wave reflection at the component surface contain information that can be used to estimate the surface shape and its position relative to the probe, which are needed to compute the imaging focal laws. The most interesting feature to extract from surfaces echoes is the Time of Flight (TOF) for each reception channel. TOF measurement in acoustic signals is a problem that frequently arises not only in Non Destructive Testing (NDT), but also in medical imaging, geophysics and other fields. The surface echo in a signal is usually identified as the first high amplitude peak, and is traditionally detected with standard methods as threshold crossing, peak search or matched filters. All these methods are easily affected by Signal to Noise Ratio, which might be high in some channels, for example if the ray arrives at the corresponding element at a low sensibility angle. Moreover, spurious echoes from bubbles, the emission signal tail or echoes from other parts of the component can be incorrectly labelled as surface echoes. This kind of outliers are difficult to filter by conventional means and, thus, there is a need for more robust surface estimation methods. In this work, we study the application of a deep 3D Convolutional Neural Network (CNN) to detect surface echoes in Full Matrix Capture (FMC) ultrasound data. The CNN is trained using signals acquired with a matrix array and a reference component, using a robotic arm set-up to measure the probe position and orientation relative to the component. Thus, with knowledge of the set-up geometry, a model is used to compute the theoretical surface echo TOFs, which are used to label the data for training. The model was tested with a validation set, presenting good agreement with the ground truth. The results were compared with the threshold crossing method observing a significant reduction of outliers in the TOF estimation.

Improving Lesion Location Reproducibility in Handheld Breast Ultrasound.

Interoperator variability in the reproducibility of breast lesions found by handheld ultrasound (HHUS) can significantly interfere with clinical care. This study analyzed the features associated with breast mass position differences during HHUS. The ability of operators to reproduce the position of small masses and the time required to generate annotations with and without a computer-assisted scanning device (DEVICE) were also evaluated. This prospective study included 28 patients with 34 benign or probably benign small breast masses. Two operators generated manual and automated position annotations for each mass. The probe and body positions were systematically varied during scanning with the DEVICE, and the features describing mass movement were used in three logistic regression models trained to discriminate small from large breast mass displacements (cutoff: 10 mm). All models successfully discriminated small from large breast mass displacements (areas under the curve: 0.78 to 0.82). The interoperator localization precision was 6.6 ± 2.8 mm with DEVICE guidance and 19.9 ± 16.1 mm with manual annotations. Computer-assisted scanning reduced the time to annotate and reidentify a mass by 33 and 46 s on average, respectively. The results demonstrated that breast mass location reproducibility and exam efficiency improved by controlling operator actionable features with computer-assisted HHUS.

Six-Degree-of-Freedom Freehand 3D Ultrasound: A Low-Cost Computer Vision-Based Approach for Orthopedic Applications.

In orthopedics, X-rays and computed tomography (CT) scans play pivotal roles in diagnosing and treating bone pathologies. Machine bulkiness and the emission of ionizing radiation remain the main problems associated with these techniques. The accessibility and low risks related to ultrasound handling make it a popular 2D imaging method. Indeed, 3D ultrasound assembles 2D slices into a 3D volume. This study aimed to implement a probe-tracking method for 6 DoF 3D ultrasound. The proposed method involves a dodecahedron with ArUco markers attached, enabling computer vision tracking of the ultrasound probe's position and orientation. The algorithm focuses on the data acquisition phase but covers the basic reconstruction required for data generation and analysis. In the best case, the analysis revealed an average error norm of 2.858 mm with a standard deviation norm of 5.534 mm compared to an infrared optical tracking system used as a reference. This study demonstrates the feasibility of performing volumetric imaging without ionizing radiation or bulky systems. This marker-based approach shows promise for enhancing orthopedic imaging, providing a more accessible imaging modality for helping clinicians to diagnose pathologies regarding complex joints, such as the shoulder, replacing standard infrared tracking systems known to suffer from marker occlusion problems.

A novel contact optimization algorithm for endomicroscopic surface scanning.

Probe-based confocal laser endomicroscopy (pCLE) offers real-time, cell-level imaging and holds promise for early cancer diagnosis. However, a large area surface scanning for image acquisition is needed to overcome the limitation of field-of-view. Obtaining high-quality images during scanning requires maintaining a stable contact distance between the tissue and probe. This work presents a novel contact optimization algorithm to acquire high-quality pCLE images. The contact optimization algorithm, based on swarm intelligence of whale optimization algorithm, is designed to optimize the probe position, according to the quality of the image acquired by probe. An accurate image quality assessment of total co-occurrence entropy is introduced to evaluate the pCLE image quality. The algorithm aims to maintain a consistent probe-tissue contact, resulting in high-quality images acquisition. Scanning experiments on sponge, ex vivo swine skin tissue and stomach tissue demonstrate the effectiveness of the contact optimization algorithm. Scanning results of the sponge with three different trajectories (spiral trajectory, circle trajectory, and raster trajectory) reveal high-quality mosaics with clear details in every part of the image and no blurred sections. The contact optimization algorithm successfully identifies the optimal distance between probe and tissue, improving the quality of pCLE images. Experimental results confirm the high potential of this method in endomicroscopic surface scanning.