Digital Image Research Articles

Data-Driven Identification unravels multiaxial mechanical response of a carbon-black filled elastomer during ageing

Under environmental exposure, the mechanical properties of elastomers change due to ageing, all while enduring mechanical service loading conditions. The influence of ageing on the multiaxial mechanical response of elastomers remains an understudied question, lacking exploration in both experimental evidence and modelling proposals. The present study describes an experimental/numerical approach to characterize the multiaxial behaviour of elastomers with consideration of ageing. This technique associates complex experimental tests conducted with a hexapod device, with a Data-Driven Identification (DDI) algorithm. Practically, heterogeneous strain fields are measured by Digital Image Correlation (DIC), and the corresponding stress and energy fields are calculated by DDI. These fields are visualized through three-dimensional maps, encompassing kinematical quantities and strain energy density. These maps convincingly capture the stiffening induced by ageing, in different deformation modes. Finally, the coupling between ageing and multiaxiality is foregathered in a material database that can be fitted for further modelling purposes.

Experimental investigation of the coupled effects of bedding planes and flaws on fracture evolution of soft bedded rocks based on 3D printing and DIC technologies

Bedded rocks are a typical geological formation with significant implications for understanding tectonic evolution, rock engineering, and geological hazard mitigation. This study introduces a novel method for fabricating bedded rocks using 3D printing (3DP) technology. By comparing the mechanical anisotropic properties and failure modes of 3DP bedded rocks with natural bedded rocks, we validate the feasibility of this approach. Compression tests are conducted on 3DP bedded rocks containing a single flaw to investigate the coupled effects of bedding planes and flaws on the mechanical properties. Digital image correlation (DIC) is employed for full-field deformation measurement during loading, enabling the study of deformation and crack evolution patterns. The results indicate that bedding planes dominate the brittleness of 3DP bedded rocks containing a single flaw. Significant plastic characteristics and prolonged nonlinear deformation stages are observed when the bedding angle (α) is between 0° and 45°, while brittleness becomes apparent beyond 45°. Both strength and elastic modulus are decided by bedding planes and initial flaws. By comparing stress–strain curves and rate of effective variance change (REVC)-strain curves, crack initiation can be quantitatively identified, revealing a linear correlation between strength and stress values at crack initiation points. The bedding plane also dominates crack propagation and failure modes: when α ≤ 30°, cracks propagate through the bedding, indicating tensile failure; when 45° ≤ α＜90°, cracks propagate along the bedding, indicating tensile-shear or shear failure; and when α = 90°, cracks propagate along bedding planes, indicating tensile failure. The findings of this study provide insights for explaining and predicting failure modes in engineering projects involving bedded rock formations, such as slopes, tunnels, and coal mines.

Characterization on fibre kinking fracture of laminated composites under combined compression and shear at high loading rate

This paper presented a novel method to characterize the fracture toughness and cohesive law of laminated composites under combined compression and shear at high loading rate. Compact compression specimens with off-axis fibres which introduce the in-plane shear stresses were conducted on the uniaxial bidirectional electromagnetic Hopkinson bar system and the displacement field and strain field were recorded by the high-speed camera for the digital image correlation analysis and J-integral calculation. The results reveal that the in-plane shear stresses bring the increase of fracture toughness at crack initiation and propagation and advance the damage initiation of the specimens. The fracture surfaces indicate that the shear stresses cause the fibre bundles' shear failure during the formation of the kink band, accompanied by more energy dissipation with the increase of off-axis angle.

Computer-aided diagnosis system for grading brain tumor using histopathology images based on color and texture features

BackgroundCancer pathology shows disease development and associated molecular features. It provides extensive phenotypic information that is cancer-predictive and has potential implications for planning treatment. Based on the exceptional performance of computational approaches in the field of digital pathogenic, the use of rich phenotypic information in digital pathology images has enabled us to identify low-level gliomas (LGG) from high-grade gliomas (HGG). Because the differences between the textures are so slight, utilizing just one feature or a small number of features produces poor categorization results.MethodsIn this work, multiple feature extraction methods that can extract distinct features from the texture of histopathology image data are used to compare the classification outcomes. The successful feature extraction algorithms GLCM, LBP, multi-LBGLCM, GLRLM, color moment features, and RSHD have been chosen in this paper. LBP and GLCM algorithms are combined to create LBGLCM. The LBGLCM feature extraction approach is extended in this study to multiple scales using an image pyramid, which is defined by sampling the image both in space and scale. The preprocessing stage is first used to enhance the contrast of the images and remove noise and illumination effects. The feature extraction stage is then carried out to extract several important features (texture and color) from histopathology images. Third, the feature fusion and reduction step is put into practice to decrease the number of features that are processed, reducing the computation time of the suggested system. The classification stage is created at the end to categorize various brain cancer grades. We performed our analysis on the 821 whole-slide pathology images from glioma patients in the Cancer Genome Atlas (TCGA) dataset. Two types of brain cancer are included in the dataset: GBM and LGG (grades II and III). 506 GBM images and 315 LGG images are included in our analysis, guaranteeing representation of various tumor grades and histopathological features.ResultsThe fusion of textural and color characteristics was validated in the glioma patients using the 10-fold cross-validation technique with an accuracy equals to 95.8%, sensitivity equals to 96.4%, DSC equals to 96.7%, and specificity equals to 97.1%. The combination of the color and texture characteristics produced significantly better accuracy, which supported their synergistic significance in the predictive model. The result indicates that the textural characteristics can be an objective, accurate, and comprehensive glioma prediction when paired with conventional imagery.ConclusionThe results outperform current approaches for identifying LGG from HGG and provide competitive performance in classifying four categories of glioma in the literature. The proposed model can help stratify patients in clinical studies, choose patients for targeted therapy, and customize specific treatment schedules.

A high explosive blast simulator

Window facades are heavily used in modern design. To ensure that the facade can withstand sufficiently large blast loads, experimental evaluation of the entire facade is crucial. In this study, we present the High Explosive Blast Simulator (HEBSim), an outdoors modular explosive-driven blast simulator with a large cross-section designed for real-size blast testing of glass facades. To evaluate the performance of HEBSim, we performed two test series, one with a rigid steel plate component and one with deformable laminated glass window components. Pressure sensors were used to measure the overpressure histories for both test series and deformation data was gathered using three-dimensional digital image correlation (3D-DIC) for the window component tests. The test series demonstrated that HEBSim generates planar and repeatable blast load profiles in line with explosive pressure resistance (EPR) classifications for various charge masses. In addition, the window component test series illustrated the stochastic fracture behavior of glass. Based on the presented data, HEBSim is found suitable for blast testing of large glass facades.

Spot test and quantitative analysis of NTO explosive by smartphone-based digital image colorimetry

Spot test and quantitative analysis of NTO explosive by smartphone-based digital image colorimetry

Role of slip in hydrogen-assisted crack initiation in Ni-based alloy 725.

We conduct in situ tensile straining experiments to investigate the role of hydrogen and slip in crack initiation in nickel-based alloy 725. Our experiments reveal no tendency for hydrogen to enhance localized slip and no necessity of slip for crack initiation. We use electrochemical charging to introduce hydrogen into samples, melt extraction to measure hydrogen content, and digital image correlation to analyze localized plastic strains during in situ tensile tests in a scanning electron microscope. Cracks initiate both in regions with and without nearby localized slip. Moreover, the fraction of cracks initiating with no nearby slip is greater at higher hydrogen content. Slip-assisted crack initiation generally occurs at locations where intergranular slip is arrested, especially at intersections of slipping coherent twin boundaries with thin twin lamellae. Cracks that initiate without nearby slip occur at a wider variety of microstructural features, including inclusions, triple junctions, and surface flaws.

Coded speckle target: Design, analysis and applications

In this paper, a novel encoding feature based on speckle patterns. It comprises three components: a pre-positioning ring, localization speckle area, and encoding speckle area. The pre-positioning ring identifies potential regions of interest. Shape function of the localization speckle area can be estimated by formulating the elliptical equation of the pre-positioning ring. Next, digital image correlation method is employed to achieve precise positioning and refine the shape function. Through the high-precision shape function, the encoded speckle area can be determined. Encoding technique utilizes a reference encoding scheme, in which each coded value region either same or is inverse to the reference region. Zero-mean normalized cross correlation relative to the reference region can be used to obtain a highly robust decoding value. Experimental results demonstrate that, despite challenges such as noise, defocus, variations in lighting intensity, and lighting uneven, the coded speckle target maintains high robustness and precise positioning accuracy. Moreover, the structure from motion and displacement measurement experiments further verifies its high accuracy in practical applications.

The role of a digital twin in supporting criminal investigations - a case report about a possible abuse.

As part of a comprehensive analysis, this case report presents a possible case of child maltreatment that can serve as a basis for forensic and medical examiner investigations. This case concerns the death of an infant who was approximately two months old. During a routine examination by the pediatrician at the end of May 2021, the child was found to have a normal head circumference of 31 cm. No other abnormalities were noted. On June 19, 2021, the child died, and an autopsy revealed a head circumference of 44 cm and a subdural hematoma as the cause of death. Questions arose as to who might have abused the child and when. The only evidence was a low-quality cell phone video taken by the child's parents on June 13, 2021, six days before the child's death, in which the child could be seen lying on a pillow. It was necessary to determine whether the child in this video already had an unnatural head circumference. This study presents a novel workflow that demonstrates how to analyze and deal with low quality video to answer questions like the above. The workflow demonstrates the creation of 3D scenes from digital image and video material. These 3D scenes can be used for object measurement and to support forensic and medical investigations. In the present case, where only low quality smartphone images were available, the presented workflow was used to create a 3D scene of the child lying on the pillow. In this 3D scene, it was possible to determine the child's head circumference. These measurements support the findings of the medical examiner (dated June 24, 2021) and confirm the suspicion that possible child abuse had already taken place on June 13, 2021. The innovative approach makes it possible to identify evidence of possible abuse based on a specific point in time, in this case the child's private footage. It also demonstrates the potential of 3D scene reconstruction in complex forensic and medical scenarios.

Intraoperative technologies to assess margin status during radical prostatectomy - a narrative review.

Positive surgical margin (PSM) is a frequent concern for surgeons performing radical prostatectomy for prostate cancer (PCa). PSM are recognized as risk factors for earlier biochemical recurrence and expose patients to adjuvant or salvage treatments such as external radiotherapy and hormonotherapy. Several strategies have been established to reduce PSM rate, while still allowing safe nerve-sparing surgery. Precise preoperative staging by multiparametric magnetic resonance imaging (mpMRI) and fusion biopsy is recommended to identify suspicious areas of extracapsular extension (ECE) that warrant special attention during dissection. However, even with optimal imaging, ECE can be missed, some cancers are not well defined or visible, and capsular incision during surgery remains an issue. Hence, intraoperative frozen section techniques, such as the neurovascular structure-adjacent frozen section examination (NeuroSAFE) have been developed and lately widely disseminated. The NeuroSAFE technique reduces PSM rate while allowing higher rate of nerve-sparing surgery. However, its use is limited to high volume or expert center because of its high barrier-to-entry in terms of logistics, human resources and expertise, as well as cost. Also, NeuroSAFE is a time-consuming process, even in expert hands. To address these issues, several technologies have been developed for an ex vivo and in vivo use. Ex vivo technology such as fluorescent confocal microscopy and intraoperative PET-CT require the extraction of the specimen for preparation, and digital images acquisition. In vivo technology, such as augmented reality based on mpMRI images and PSMA-fluorescent guided surgery have the advantage to provide an intracorporeal analysis of the completeness of the resection. The current manuscript provides a narrative review of established techniques, and details several new and promising techniques for intraoperative PSM assessment.

Exploring Stone Material Behavior and Damage Analysis with Digital Image Correlation

Exploring Stone Material Behavior and Damage Analysis with Digital Image Correlation

Effects of local strain on the plastic deformation and fracture mechanism of heterogeneous multilayered aluminum

Elucidating the effect of local strain on the mechanical properties is of great significance for the design of high-performance layered metals. For this purpose, we conceived the present study, featured by tailoring the local strain by layer thickness design, and simultaneous monitoring of local strain and geometrically necessary dislocations (GNDs) via coupling in-situ electron backscatter diffraction (EBSD) and high-resolution digital image correlation (DIC). In addition, synchrotron X-ray micro-computed tomography (μCT) was employed to analyze the microcracks that serve as another form of strain localization. Such detailed experimental studies revealed that the interfacial strain gradient was rapidly elevated, and the strain localization band was effectively dispersed as the layer thickness decreased. This leads to two typical transitions, from grain-boundary-related to layer-interface-related plastic deformation mode, and from macroscopic shear to zig-zag fracture mode. Their influences on the mechanical properties, as well as underlying mechanisms, were discussed based on the relationship among the layer thickness, strain gradient, strain localization, GND density, and microcracks. Our work not only contributes to the fundamental understanding of the mechanical behavior of multilayered metals but also offers guidance for the structural design of high-performance metals aimed at achieving superior strength-ductility combinations.

Assessment of Digital Image Correlation Effectiveness and Quality in Determination of Surface Strains of Hybrid Steel/Composite Structures.

The application of the digital image correlation (DIC) contactless method has extended the possibilities of reliable assessment of structure strain fields and deformations throughout the last years. However, certain weak points in the analyses using the DIC method still exist. The fluctuations of the results caused by different factors as well as certain deficiencies in the evaluation of DIC accuracy in applications for hybrid steel/composite structures with adhesive joints are one of them. In the proposed paper, the assessment of DIC accuracy based on the range of strain fluctuation is proposed. This relies on the use of a polynomial approximation imposed on the results obtained from the DIC method. Such a proposal has been used for a certain correction of the DIC solution and has been verified by the introduction of different error measures. The evaluation of DIC possibilities and accuracy are presented on the examples of the static tensile tests of adhesively bonded steel/composite joints with three different adhesives applied. The obtained results clearly show that in a non-disturbed area, very good agreement between approximated DIC and FEM results is achieved. The relative average errors in an area, determined by comparison of DIC and FEM strains, are below 15%. It is also observed that the use of approximated strains by polynomial function leads to a more accurate solution with respect to FEM results. It is concluded that DIC can be successfully applied for the analyses of hybrid steel/adhesive/composite samples, such as determination of strain fields, non-contact visual detection of faults of manufacturing and their development and influence on the whole structure behavior during the strength tests, including the elastic response of materials.

Digital whole-slide imaging of changes in amyloid after peripheral blood stem cell transplantation in patients with amyloid light-chain amyloidosis.

Peripheral blood stem cell transplantation (PBSCT) has made amyloid light-chain (AL) amyloidosis treatable. After PBSCT, hematological complete remission (HCR) can be achieved, leading to improved renal prognosis. The purpose of this study was to evaluate whether whole slide imaging of biopsy samples shows a post-treatment reduction in amyloid deposits in patients with AL amyloidosis. Patients were divided into three groups: Group A (n = 8), not eligible for PBSCT and treated with other therapies; Group B (n = 11), treated with PBSCT and achieved HCR; and Group C (n = 5), treated with PBSCT but did not achieve HCR. Clinical findings and amyloid deposition in glomeruli, interstitium, and blood vessels were compared before and after treatment using digital whole-slide imaging. Proteinuria and hypoalbuminemia improved more in Group B than in the other groups, and in Group B, amyloid deposition improved more in the glomeruli than in the interstitium and blood vessels. The long-term renal and survival prognosis was better in Group B than in the other groups. PBSCT can be expected to improve long-term clinical and renal histological prognosis in patients with AL amyloidosis who achieve HCR. Amyloid disappearance from renal tissue may take a long time even after clinical HCR.

Open Access Data and Deep Learning for Cardiac Device Identification on Standard DICOM and Smartphone-based Chest Radiographs.

"Just Accepted" papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. Purpose To develop and evaluate a publicly available deep learning model for segmenting and classifying cardiac implantable electronic devices (CIEDs) on Digital Imaging and Communications in Medicine (DICOM) and smartphone-based chest radiograph (CXR) images. Materials and Methods This institutional review board-approved retrospective study included patients with implantable pacemakers, cardioverter defibrillators, cardiac resynchronization therapy devices, and cardiac monitors who underwent chest radiography between January 2012 and January 2022. A U-Net model with a ResNet-50 backbone was created to classify CIEDs on DICOM and smartphone images. Using 2,321 CXRs from 897 patients (median age, 76 years (range 18-96 years); 625 male, 272 female), CIEDs were categorized into four manufacturers, 27 models, and one 'other' category. Five smartphones were used to acquire 11,072 images. Performance was reported using the Dice coefficient on the validation set for segmentation or balanced accuracy on the test set for manufacturer and model classification, respectively. Results The segmentation tool achieved a mean Dice coefficient of 0.936 (IQR: 0.890-0.958). The model had an accuracy of 94.36% (95% CI: 90.93%-96.84%; n = 251/266) for CIED manufacturer classification and 84.21% (95% CI: 79.31%-88.30%; n = 224/266) for CIED model classification. Conclusion The proposed deep learning model, trained on both traditional DICOM and smartphone images, showed high accuracy for segmentation and classification of CIEDs on CXRs. ©RSNA, 2024.

Deep Learning in Cardiothoracic Ratio Calculation and Cardiomegaly Detection.

Objectives: The purpose of this study is to evaluate the performance of our deep learning algorithm in calculating cardiothoracic ratio (CTR) and thus in the assessment of cardiomegaly or pericardial effusion occurrences on chest radiography (CXR). Methods: From a database of 8000 CXRs, 13 folders with a comparable number of images were created. Then, 1020 images were chosen randomly, in proportion to the number of images in each folder. Afterward, CTR was calculated using RadiAnt Digital Imaging and Communications in Medicine (DICOM) Viewer software (2023.1). Next, heart and lung anatomical areas were marked in 3D Slicer. From these data, we trained an AI model which segmented heart and lung anatomy and determined the CTR value. Results: Our model achieved an Intersection over Union metric of 88.28% for the augmented training subset and 83.06% for the validation subset. F1-score for subsets were accordingly 90.22% and 90.67%. In the comparative analysis of artificial intelligence (AI) vs. humans, significantly lower transverse thoracic diameter (TTD) (p < 0.001), transverse cardiac diameter (TCD) (p < 0.001), and CTR (p < 0.001) values obtained using the neural network were observed. Conclusions: Results confirm that there is a significant correlation between the measurements made by human observers and the neural network. After validation in clinical conditions, our method may be used as a screening test or advisory tool when a specialist is not available, especially on Intensive Care Units (ICUs) or Emergency Departments (ERs) where time plays a key role.

Study on the strength mechanism of the wooden round-end mortise-and-tenon joint using the digital image correlation method

Abstract The aim of this study was to reveal the strength mechanism of the mortise-and-tenon (M–T) joint at a deeper level. The effects of tenon fit on bending and withdrawal load resistances, and strain distributions outside and inside beech (Fagus sylvatica) wooden round-end M–T joints were experimentally investigated using mechanical testing synchronizing digital image correlation method (DICM). The results showed that (1) the tenon fit had greater significance on withdrawal properties than that of bending properties of M–T joints; (2) the bending load resistance was linearly proportional to withdrawal load resistance based on both theoretic analysis and regression methods; (3) strain distributions outside M–T joints during the loading process were not sufficient to evaluate the mechanical behaviors of the M–T joint; (4) strain distributions inside M–T joints showed that the maximum strains on top and bottom parts of the tenon were significantly greater than that of middle part, but the difference decreased with the growth of tenon fit; (5) the method of determining the optimal tenon fit of the M–T joint based on the DICM was proposed, and optimal tenon fit of beech wooden round-end M–T joint evaluated ranged from 0.4 to 0.5 mm.

Deformation and failure behavior of 2024-T42 sheet under impact loading

The deformation and failure behavior of 2024-T42 aluminum alloy sheet was investigated through a combined experimental-numerical method. Nine types of specimens were designed to cover a wide range of stress triaxialities and strain rates. Quasi-static and dynamic tests were carried out by electronic testing machine and split Hopkinson tensile bar respectively, and digital image correlation (DIC) method was introduced to measure the deformation. The phenomenological damage model GISSMO (generalized incremental stress state dependent damage model) and Johnson-Cook model were adopted to simulate all of the above tests and the load-displacement curves through numerical simulation were derived. An optimization method was developed to obtain all the model parameters by matching the load-displacement curves from simulation with those from tests by LS-OPT. Finally, drop weight tests and tensile tests of the central-hole plate were conducted. The applicability and accuracy of the damage models were verified by comparing the simulation results with the experiments, which indicates that GISSMO model predicts better the tests than the Johnson-Cook failure model.

Models and methods of object detection in digital image processing

Object detection in digital images can face such problems that arise in the process of image registration as the presence of noise, low image quality/resolution, illumination heterogeneity, overlapping objects, and others. These problems complicate the process of object detection and lead to errors in image processing algorithms. To solve these problems, we study the advantages, disadvantages, and technical features of models and methods for detecting objects in digital images for their reasonable selection in practical applications. Figs. 2. Refs. 11 titles.

Covert Communication for Dual Images with Two-Tier Bits Flipping

Data hiding in digital images is a potent solution for covert communication, embedding sensitive data into cover images. However, most existing methods are tailored for one-to-one scenarios, which present security risks. To mitigate this vulnerability, we introduce an innovative one-to-two data hiding scheme that employs a two-tier bit-flipping strategy to embed sensitive data in dual images. This process produces two stego images which are then transmitted to two distinct recipients who cannot extract any sensitive data alone. The sensitive data can only be extracted when the two recipients trust each other. Through this method, we can secure the stego images. The experimental results illustrate that our method achieves an excellent data payload while maintaining high visual quality.