Imaging Plate Research Articles

Medical expert and machine learning analysis of lumbar disc herniation based on magnetic resonance imaging

ObjectiveObservation and statistical analysis was used to evaluate the ability of lumbar disc magnetic resonance imaging (MRI) to obtain the smallest size of Al2O3 spots (calcified foci) and lumbar disc fiber signals. MethodsFirst, we perform image acquisition of the MRI, perform the statistical analysis using five different sizes of Al2O3 spots and lumbar disc fibers on the imaging plate (IP), use a molybdenum target MRI machine 26 kV, adjust the milliampere amount, select the appropriate image processing parameters, and obtain the experimental image of the density value (D=0.70±0.05), the 5-point judgment method is used to obtain the total score of 10 lines of signals composed of 5 signals and noise, and a group is computed using the statistical analysis that is built from human observation and machine prediction (based on machine learning), which are then compared. In particular, we implemented a convolutional neural network algorithm to evaluate the medical condition against human observers, so as to study the structure of the lumbar intervertebral disc. We compute the true positive probability P(S/s) and false positive probability P(S/n) values, draw ROC curve, and compute the judgment probability value of each signal Pdet. We then use SPSS 10.0 statistical single factor analysis of variance software to process the data, and obtain the smallest calcified focus and lumbar disc mass focus. ResultsUsing probability statistical methods to obtain the data of the ROC curve and the average value of the judgment probability Pdet, among 5 different sizes Al2O3 spots (calcifications), 0.20mm Pdet= 0.6250minimum, 0.55mm Pdet = 0.9000 the largest, but the difference between 0.20mm and 0.25mm Pdet is not statistically significant, and the difference is statistically significant; among the five types of lumbar disc fibers (tumor foci) of different sizes, 0.45mm Pdet= 0.5313minimum, 1.00mm Pdet =0.8813 is the largest, while the difference between 0.45mm and 0.60mm is not statistically significant, and the difference between 0.45mm and other is statistically significant. We note that the human observation and machine learning prediction is not significantly different (P<0.05). ConclusionsThe computation of the ROC curve and that of the probability of judgment using the statistical analysis based on a deep learning platform is simple and fast, and approximates that of human observation. It is suitable for the evaluation of image quality control carried out by daily clinical work.

Coupling picodroplet microfluidics with plate imaging for the rapid creation of biomanufacturing suitable cell lines with high probability and improved multi-step assurance of monoclonality.

There is an expectation from regulatory agencies that cell lines used in the commercial production of biopharmaceuticals are derived from a single cell progenitor. Traditional methods of single cell cloning include the use of the limiting dilution cloning method which often requires multiple rounds of low cell density cell plating and either microscopic evaluation that wells contain single cells and/or the calculation of a statistically derived probability of monoclonality. We have combined the single cell screening, deposition and picodroplet imaging ability of Sphere Fluidics' Cyto-Mine technology with the plate imaging capability of the Solentim Cell Metric to create a novel workflow for the generation of high producing clonal cell lines with both high probability and assurance of monoclonality. The efficiency of three key stages of the process (single cell picodroplet encapsulation, single picodroplet dispensation and single cell settling in the focal plane of the plate imager) was determined and a probability calculation was derived using the Wilson Score Interval method. The combined probability that a single cell is encapsulated into a picodroplet, is deposited into the correct well of a 96-well plate and that a cell settles into the focal plane of the plate imager yields a combined>99% probability of monoclonality. Furthermore, visual verification of a single cell progenitor is obtained at multiple steps throughout the cloning workflow. This novel methodology for the rapid creation of high quality clonal cell lines for biomanufacturing purposes has many advantages over more traditional approaches including improved assurance of single cell derivation, integrated imaging capability, assay flexibility, equipment utilization time and in-process cell line segregation.

Line imaging of a terahertz zero-order Mathieu-Gauss beam.

Thestudy of terahertz (THz) structured beams has become an interesting subject. Here, we use 3D printed diffractive plates to generate a THz zero-order Mathieu-Gauss beam at a frequency of 0.1 THz and simulate its line-imaging effect. According to the nondiffraction property of the beam, we conduct a transmission imaging test by placing the imaging plate at different positions along the direction of beam propagation. The results show that the THz zero-order Mathieu-Gauss beam has a good imaging effect in the depth of field of about 130-380 mm. This can be used in large depth of field THz line imaging.

Visualization of pH Distributions inside the Crevice of Stainless Steel in Corrosive Environments

Stainless steels are known for its excellent corrosion resistance. However, stainless steels sometime suffer from crevice corrosion in chloride environments. The distribution of pH inside the crevice is recognized to be the important factor in crevice corrosion of stainless steels [1, 2]. This study focused on visualization of pH inside the crevice in corrosive environments.An imaging plate was prepared by a sol-gel method. Ethyl violet was used to assess the pH values. The fabricated imaging plates were calibrated by 0.01 M NaCl solution at pH 0.0, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, and 4.0. The imaging plate was immersed in the 0.01 M NaCl solutions, and the color change was observed by an optical microscope. Type 304 stainless steel (Fe-18mass%Cr-8mass%Ni) was used as the specimens. The size of the specimen for the crevice corrosion test is 3 mm × 3 mm×17 mm. The specimen surfaces were polished with a 1 µm diamond paste. The scan rate of potentiodynamic polarization measurements was set to 23mV min- 1. The specimen for the polarization measurements is 17 mm × 25 mm × 3 mm in size. The electrode area was 1 cm2. The electrolyte used for the potentiodynamic polarization was 0.01 M NaCl (pH 3.0). The electrolyte was deaerated before the polarization measurements. The reference electrode was Ag/AgCl (3.33 M KCl). The counter electrode was Pt. The crevice corrosion tests were performed under a potentiostatic polarization. The applied potential was 0.3 V. The crevice was made between the steel surface (3 mm × 3 mm) and the imaging plate. Optical microscope images of the surface were taken every 30 seconds. The pH values inside the crevice were calculated from the R (red), G (green), and B (blue) values of each pixel in the images.In calibration, the color of the imaging plate changed from violet to yellow, suggesting that G values of imaging plate mainly responded to pH. The pitting potential of the specimens was 0.4 V. Therefore, 0.3 V was suitable for the crevice corrosion test. Because 0.3 V (Ag/AgCl (3.33 M KCl)) was lower than the pitting potential. The visualization of pH in the crevice corrosion was conducted. The pH decreased during the incubation, initiation, and growth of crevice corrosion. The pH was the important factor in the initiation and growth of crevice corrosion.[1] T. Kaji, T. Sekiai, I. Muto, Y. Sugawara, N. Hara, Visualization of pH and pCl Distributions: Initiation and Propagation Criteria for Crevice Corrosion of Stainless Steel, J. Electrochem. Soc., 159 (2012), C289-C297.[2] M. Nishimoto, J. Ogawa, I. Muto, Y. Sugawara, N. Hara, Simultaneous visualization of pH and Cl- distributions inside the crevice of stainless steel, Corros. Sci., 106 (2016), 298-302.

Penentuan Peak Kilovoltage (kVp) Pesawat Sinar-X Dengan Pemanfaatan Imaging Plate (IP) Di RSUD Dr. Moewardi

&lt;p&gt;Research has been carried out to determine the kVp of X-ray aircraft using an imaging plate (IP) as a measuring tool. The imaging plate functions to record images after irradiation and as a detector to capture and store X-ray energy when it penetrates an object. The purpose of this study is to use IP as a kVp measurement tool. The method used is to create a characteristic curve of the relationship between the ratio of Region of Interest (ROI) of two aluminum filters to rated voltage (kVp). From the research obtained the equation y = 2816.61 x2 – 4532.19 x + 1878.65 with R2 = 0.988. The kVp test was carried out using a fluoroscopic X-ray model SM-20HFH. The test results obtained that the measured kVp value at a voltage of 70 kV was 66.21 kV and an error value of 5.41%. While the measured kVp value at 55 kV is 58.95 kV with an error value of -7.18%. These results indicate that IP can be used to measure kVp with an error below the allowable tolerance, namely the max error ≤ of 10%.&lt;/p&gt;

The suitability of high throughput automated patch clamp for physiological applications.

Although automated patch clamp (APC) devices have been around for many years and have become an integral part of many aspects of drug discovery, high throughput instruments with gigaohm seal data quality are relatively new. Experiments where a large number of compounds are screened against ion channels are ideally suited to high throughput APC, particularly when the amount of compound available is low. Here we evaluate different APC approaches using a variety of ion channels and screening settings. We have performed a screen of 1920 compounds on GluN1/GluN2A NMDA receptors for negative allosteric modulation using both the SyncroPatch 384 and FLIPR. Additionally, we tested the effect of 36 arthropod venoms on NaV 1.9 using a single 384-well plate on the SyncroPatch 384. As an example for mutant screening, a range of acid-sensing ion channel variants were tested and the success rate increased through fluorescence-activated cell sorting (FACS) prior to APC experiments. Gigaohm seal data quality makes the 384-format accessible to recording of primary and stem cell-derived cells on the SyncroPatch 384. We show recordings in voltage and current clamp modes of stem cell-derived cardiomyocytes. In addition, the option of intracellular solution exchange enabled investigations into the effects of intracellular Ca2+ and cAMP on TRPC5 and HCN2 currents, respectively. Together, these data highlight the broad applicability and versatility of APC platforms and also outlines some limitations of the approach. KEY POINTS: High throughput automated patch clamp (APC) can be used for a variety of applications involving ion channels. Lower false positive rates were achieved using automated patch clamp versus a fluorometric imaging plate reader (FLIPR) in a high throughput compound screen against NMDA receptors. Genetic variants and mutations can be screened on a single 384-well plate to reduce variability of experimental parameters. Intracellular solution can be perfused to investigate effects of ions and second messenger systems without the need for excised patches. Primary cells and stem cell-derived cells can be used on high throughput APC with reasonable success rates for cell capture, voltage clamp measurements and action potential recordings in current clamp mode.

Automatic Inhibition Zone Diameter Measurement for Disc Diffusion Test Using Image Segmentation

Automation of Antimicrobial Susceptibility Test (AST) for faster results and the cheaper cost is gaining importance for effective medical diagnosis. Among all the available methods for AST, disk diffusion is the cheaper one, requires less skill, and it is applicable for telemetry. The diameters of the Inhibition zones are calculated using image processing and computer vision techniques to provide easy and automated data for further processing, however, the result of a particular antibiotic is Susceptible (S), Intermediate (I), or resistance (R). In this paper, the agar plate images, which were prepared for the AST, have been taken with 23 antibiotics and 12 bacteria and the image bank of about 170 images with 513 inhibition zones has been developed. For the diameter calculation of the inhibition zones, four methods are developed. In the first method, the diameter is calculated using the watershed segmentation method which requires manual interference, in the second method, modified edge detection is used instead of edge detection in the watershed segmentation, in the third method a semi-automatic method is developed using segmentation with active contours, and in the fourth one, an automatic method is used based on the fuzzy clustering along with Level set methods (FCLSM). The evaluation is done using kappa and correlation indices. The results show that these methods are giving better results within the tolerable limits for automation. In this paper, the same agar plate image with 11 antibiotics is taken to compare developed methods with the manual method and satisfying results are obtained.

Longitudinal FRET Imaging of Glucose and Lactate Dynamics and Response to Therapy in Breast Cancer Cells.

The reprogramming of cellular metabolism is a hallmark of cancer. The ability to noninvasively assay glucose and lactate concentrations in cancer cells would improve our understanding of the dynamic changes in metabolic activity accompanying tumor initiation, progression, and response to therapy. Unfortunately, common approaches for measuring these nutrient levels are invasive or interrupt cell growth. This study transfected FRET reporters quantifying glucose and lactate concentration into breast cancer cell lines to study nutrient dynamics and response to therapy. Two FRET reporters, one assaying glucose concentration and one assaying lactate concentration, were stably transfected into the MDA-MB-231 breast cancer cell line. Correlation between FRET measurements and ligand concentration were measured using a confocal microscope and a cell imaging plate reader. Longitudinal changes in glucose and lactate concentration were measured in response to treatment with CoCl2, cytochalasin B, and phloretin which, respectively, induce hypoxia, block glucose uptake, and block glucose and lactate transport. The FRET ratio from the glucose and lactate reporters increased with increasing concentration of the corresponding ligand (p < 0.005 and p < 0.05, respectively). The FRET ratio from both reporters was found to decrease over time for high initial concentrations of the ligand (p < 0.01). Significant differences in the FRET ratio corresponding to metabolic inhibition were found when cells were treated with glucose/lactate transporter inhibitors. FRET reporters can track intracellular glucose and lactate dynamics in cancer cells, providing insight into tumor metabolism and response to therapy over time.

DETECÇÃO E RECONHECIMENTO DE PLACAS DE LICENCIAMENTO VEICULAR EM TEMPO REAL USANDO CNN

Brazil has a large fleet of vehicles running daily along urban roads and highways, which requires the use of some computational solution to assist in control and management. In this work we developed an application to detect and recognize real-time licenseplates with various application possibilities. The methodology developed in this work has three main stages: plate detection, character segmentation and recognition. For the detection step we used the YOLO library, which makes use of machine learning techniques to detect objects in real time. YOLO was trained using a dataset with plate images in different environments. In the segmentation stage, the individual characters contained in the plate were separated, using image processing methods. In the last stage, character recognition was performed using two convolutional neural networks, obtaining a hit rate of 83.33%.

RETRACTED ARTICLE: Improved CNN license plate image recognition based on shark odor optimization algorithm

RETRACTED ARTICLE: Improved CNN license plate image recognition based on shark odor optimization algorithm

Systematic Study on Morphological, Electrochemical Impedance, and Electrocatalytic Activity of Graphitic Carbon Nitride Modified on a Glassy Carbon Substrate from Sequential Exfoliation in Water.

Several researchers have synthesized graphitic carbon nitride (GCN) from various precursors and attached it to electrode substrates after exfoliation under different conditions and have reported inconsistent data on electrochemical impedance, electroactive surface areas, and electrocatalytic activity. Thus, the present study aims to study the same systematically in addition to morphology after modifying GCN on the GC substrate from different exfoliation times in water assisted by sonication. The GCN was prepared from urea by bulk condensation pyrolysis and then attached to the GC substrate by drop casting to study its morphology, electrochemical impedance, and electrocatalytic activity with respect to exfoliation. The SEM image of a GCN-modified GC plate after 15 and 30 min of exfoliation shows bulky structure whereas thin sheets of GCN were noticed after 120 min of exfoliation. On the other hand, broken sheets were observed when GCN was coated from beyond 120 min of exfoliation. The electrochemical impedance studies show that the charge transfer resistance (RCT) of GCN modified from 15 and 30 min of exfoliation was higher than that for the bare GC electrode. However, it started to decrease while increasing the exfoliation time, and 1.8 kΩ was obtained after 120 min of exfoliation. The RCT value was again increased to 3.2 and 5.0 kΩ for GCN coated after 150 and 180 min of exfoliation, respectively. The electroactive surface area (EASA) of GCN modified by 15 and 30 min of exfoliation was less than that of the bare GC electrode, whereas it was 3.8-fold higher for GCN coated from 120 min of exfoliation. The electrocatalytic activity of the GC electrodes modified with GCN was then tested by studying ascorbic acid (AA) and dopamine (DA) oxidation and reduction of hydrogen peroxide (HP). Among the different exfoliation times, GCN modified from 120 min of exfoliation displayed the highest electrocatalytic activity toward AA, DA, and HP. This was attributed to its higher EASA and lower charge-transfer resistance.

Efficient Selection of Recombinant Fluorescent Vaccinia Virus Strains and Rapid Virus Titer Determination by Using a Multi-Well Plate Imaging System.

Engineered vaccinia virus (VACV) strains are used extensively as vectors for the development of novel cancer vaccines and cancer therapeutics. In this study, we describe for the first time a high-throughput approach for both fluorescent rVACV generation and rapid viral titer measurement with the multi-well plate imaging system, IncuCyte®S3. The isolation of a single, well-defined plaque is critical for the generation of novel recombinant vaccinia virus (rVACV) strains. Unfortunately, current methods of rVACV engineering via plaque isolation are time-consuming and laborious. Here, we present a modified fluorescent viral plaque screening and selection strategy that allows one to generally obtain novel fluorescent rVACV strains in six days, with a minimum of just four days. The standard plaque assay requires chemicals for fixing and staining cells. Manual plaque counting based on visual inspection of the cell culture plates is time-consuming. Here, we developed a fluorescence-based plaque assay for quantifying the vaccinia virus that does not require a cell staining step. This approach is less toxic to researchers and is reproducible; it is thus an improvement over the traditional assay. Lastly, plaque counting by virtue of a fluorescence-based image is very convenient, as it can be performed directly on the computer.

Experimental analysis of mechanical behaviour and residual stresses of EN-36C alloy steel with and without tempering

The intense demands of nickel chromium case hardened steel (EN-36C) alloy steel in different engineering applications are increasing day by day due to its cheap and easy availability. The effect of different stages of tempering on EN-36C alloy steel has been carried out to check the mechanical behavioural, microstructural properties and residual stresses in the present work. The effect of tempering on response variables viz., material removal rate, surface roughness, tool tip temperature and residual stresses are evaluated. The cosα method is used to measure the residual stresses in the specimen using two-dimensional detectors such as imaging plates. Further, the influence of tempering on mechanical properties such as tensile strength, hardness, toughness and percentage elongation has been observed. Experimental results depicted that the ductility and toughness are improved without significant change in hardness in the specimen tempered at 500°C. The mechanical properties of specimens tempered at 500°C are found to be a tensile strength of 680.42 MPa, hardness 92 Rockwell hardness of scale B and toughness 187 J. The maximum value of material removal rate (12596.80 mm3/min), minimum tool tip temperature (61.33°C), average surface roughness ( Ra = 1.93, Rq = 2.36, Rz = 10.30) and lowest residual stress 217 MPa are observed in the specimens tempered at 500°C.

Robust deep learning optical autofocus system applied to automated multiwell plate single molecule localization microscopy.

We presenta robust, long-range optical autofocus system for microscopy utilizing machine learning. This can be useful for experiments with long image data acquisition times that may be impacted by defocusing resulting from drift of components, for example due to changes in temperature or mechanical drift. It is also useful for automated slide scanning or multiwell plate imaging where the sample(s) to be imaged may not be in the same horizontal plane throughout the image data acquisition. To address the impact of (thermal or mechanical) fluctuations over time in the optical autofocus system itself, we utilize a convolutional neural network (CNN) that is trained over multiple days to account for such fluctuations. To address the trade-off between axial precision and range of the autofocus, we implement orthogonal optical readouts with separate CNN training data, thereby achieving an accuracy well within the 600nm depth of field of our 1.3 numerical aperture objective lens over a defocus range of up to approximately +/-100μm. We characterize the performance of this autofocus system and demonstrate its application to automated multiwell plate single molecule localization microscopy.

License Plate Image Reconstruction Based on Generative Adversarial Networks

License plate image reconstruction plays an important role in Intelligent Transportation Systems. In this paper, a super-resolution image reconstruction method based on Generative Adversarial Networks (GAN) is proposed. The proposed method mainly consists of four parts: (1) pretreatment for the input image; (2) image features extraction using residual dense network; (3) introduction of progressive sampling, which can provide larger receptive field and more information details; (4) discriminator based on markovian discriminator (PatchGAN) can make a more accurate judgment, which guides the generator to reconstruct images with higher quality and details. Regarding the Chinese City Parking Dataset (CCPD) dataset, compared with the current better algorithm, the experiment results prove that our model has a higher peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) and less reconstruction time, which verifies the feasibility of our approach.

IOT and Machine Learning based Automatic Toll Collection System

Automatic Toll Collection System is a wireless system which autmomatically collects the toll charge to vehicle at various toll booths in many metropolitian cities. It is very efficient and fast processing technology which will eliminate heavy congestion and over crowding of vehicles in cities. It accelerates hassle free toll collection system and traffic monitoring. This system detects the arrival of vehicle and then captures the image of number plate.

Automatic Number Plate Recognition Using Image Processing

Automatic Number Plate Recognition (ANPR) is a mass surveillance system that captures the image of vehicles and recognizes their registration number issued by government. ANPR is often used in the detection of stolen vehicles, traffic surveillance system. Our project presents a model in which the vehicle license plate image is obtained by the digital cameras and the image is processed to get the number plate information. A vehicle image is captured and processed using various methods. Vehicle number plate region is extracted using the deep neural networks. Optical character recognition is implemented using certain machine learning algorithms for the character recognition. The system is implemented using deep neural network model, machine learning algorithms and is simulated in python, and its performance is tested on real images. It is observed that the developed model successfully detects the license plate region and recognizes the individual characters. There are various recognition strategies that have been produced and number plate recognition systems are today used in different movement and security applications, such as access and border control, parking, or tracking of stolen vehicles.

Compact spectroscopy of keV to MeV X-rays from a laser wakefield accelerator

We reconstruct spectra of secondary X-rays from a tunable 250–350 MeV laser wakefield electron accelerator from single-shot X-ray depth-energy measurements in a compact (7.5 × 7.5 × 15 cm), modular X-ray calorimeter made of alternating layers of absorbing materials and imaging plates. X-rays range from few-keV betatron to few-MeV inverse Compton to > 100 MeV bremsstrahlung emission, and are characterized both individually and in mixtures. Geant4 simulations of energy deposition of single-energy X-rays in the stack generate an energy-vs-depth response matrix for a given stack configuration. An iterative reconstruction algorithm based on analytic models of betatron, inverse Compton and bremsstrahlung photon energy distributions then unfolds X-ray spectra, typically within a minute. We discuss uncertainties, limitations and extensions of both measurement and reconstruction methods.

Recognition of Vehicle License Plates Based on Image Processing

In this study, we have proposed an algorithm that solves the problems which occur during the recognition of a vehicle license plate through closed-circuit television (CCTV) by using a deep learning model trained with a general database. The deep learning model which is commonly used suffers with a disadvantage of low recognition rate in the tilted and low-resolution images, as it is trained with images acquired from the front of the license plate. Furthermore, the vehicle images acquired by using CCTV have issues such as limitation of resolution and perspective distortion. Such factors make it difficult to apply the commonly used deep learning model. To improve the recognition rate, an algorithm which is a combination of the super-resolution generative adversarial network (SRGAN) model, and the perspective distortion correction algorithm is proposed in this paper. The accuracy of the proposed algorithm was verified with a character recognition algorithm YOLO v2, and the recognition rate of the vehicle license plate image was improved 8.8% from the original images.

Characterization of Agfa Structurix series D4 and D3sc x-ray films in the 0.7-4.6 keV energy range.

X-ray films remain a key asset for high-resolution x-ray spectral imaging in high-energy-density experiments conducted at the National Ignition Facility (NIF). The soft x-ray Opacity Spectrometer (OpSpec) fielded at the NIF has an elliptically shaped crystal design that measures x rays in the 900-2100eV range and currently uses an image plate as the detecting medium. However, Agfa D4 and D3sc x-ray films' higher spatial resolution provides increased spectral resolution to the data over the IP-TR image plates, driving the desire for regular use of x-ray film as a detecting medium. The calibration of Agfa D4 x-ray film for use in the OpSpec is communicated here. These calibration efforts are vital to the accuracy of the NIF opacity measurements and are conducted in a previously un-studied x-ray energy range under a new film development protocol required by NIF. The absolute response of Agfa D4 x-ray film from 705 to 4620eV has been measured using the Nevada National Security Site Manson x-ray source. A broader range of energies was selected to compare results with previously published data. The measurements were taken using selected anodes, filters, and applied voltages to produce well-defined energy lines.