Images Of Sections Research Articles

A novel and biocompatible photopolymerizable resin based on cyclohexanedimethanol‐dimetacrylate designed to light‐print microneedles

AbstractMicroneedles offer a promising avenue for painless drug delivery through micro‐perforation, and additive manufacturing, particularly stereolithography, has proven effective for their fabrication. This study focuses on developing a novel biocompatible resin for 3D printing microneedles. Spectroscopic methods are employed to confirm the structures of all intended resin monomers, with a specific analysis of the crystallographic structure of cyclohexanedimethanol methacrylate (CDMM) using x‐ray diffraction. The results indicate that CDMM crystallizes in the monoclinic system, aligning with the P21/c space group. The fabricated conical microneedles, standing at approximately 655 μm in height, underwent thorough mechanical and thermal characterization. Depth analyses of micro‐perforations in Parafilm M and pig skin were performed using optical coherence tomography and histological sections, demonstrating successful penetration through the stratum corneum and epidermal layers into the superficial dermal layer (1.5–4 mm thickness) without affecting nerve endings. Cytocompatibility tests affirm the biocompatibility of the microneedles. This work highlights the potential of the newly developed biocompatible material for printable drug delivery systems, emphasizing microneedles and other implant forms.

The Impact of Nasal Septum Deviation on Paranasal Sinus Volumes

Objective: This study examined the impact of nasal septum deviation on the volumes of four pairs of paranasal sinuses: sinus frontalis, sinus maxillaris, sinus sphenoidalis, and cellulae ethmoidales. These cavities are formed by the invagination of the nasal mucosa into bones and vary greatly in shape and size. Their location is crucial in the pathogenesis of regional diseases, and anatomical variations are frequently observed in humans. Computed Tomography imaging provides excellent soft tissue differentiation, which is essential for diagnosing sinonasal disorders. Cavalieri’s principle enables rapid and accurate measurement of sinus volumes using sectional images. The aim of our study was to retrospectively examine the impact of nasal septum deviation on paranasal sinus volumes in relation to age and gender. Material and Method: The study reviewed computed tomography images of participants who visited Tokat Gaziosmanpaşa University Hospital using The Picture Archiving and Communication System. A total of 281 participants, comprising 151 women and 130 men, were included in the study. The participants were divided into four age groups: 0–17, 18–45, 46–65, and over 65. The computed tomography images related to the paranasal sinuses were listed, and the interior of the volume to be measured was colored using ImageJ software. The volume of each sinus was calculated using Cavalieri’s principle. Results: Upon examination of all sinuses, it was observed that men had larger sinus volumes than women (p0.05). Conclusion: Quantitatively measuring the volumes of paranasal sinuses in a short period and determining their relationship with nasal septum deviation will facilitate surgical planning in the future. It may provide some advantages for surgeons.

Unveiling tumor invasiveness: enhancing cancer diagnosis with phase-contrast microtomography for 3D virtual histology

Malignant diseases are characterized by a critical trait known as invasiveness, where tumor cells tend to spread from the primary tissue layer into surrounding healthy tissues and distant organs. Presently, histopathology offers essential insights for diagnosing, classifying, predicting outcomes, and guiding patient-specific treatments. However, histology offers two-dimensional data from chosen cutting planes. Although 3D histological volumes can be generated through serial sectioning or whole slide imaging, this method is laborious, may introduce processing artefacts, and lacks isotropic spatial resolution. These limitations pose a considerable challenge to accurate diagnoses, particularly when dealing with micro-infiltrating carcinomas. These lesions, characterized by minute infiltrations, demand a three-dimensional representation for comprehensive visualization, essential for precise identification and assessment. Emerging X-ray-based virtual histology technology offers three-dimensional visualization of soft-tissue specimens, enabling virtual slicing in any direction or at any point. This approach can assist in guiding tissue sectioning for optimal representation of tumor cross sections during histological analysis. Micro-infiltrating carcinomas from the breast, cervix, and thyroid were imaged using X-ray phase-contrast microtomography (PhC-μ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mu$$\\end{document}CT) at the Elettra synchrotron facility in Trieste, Italy. Comparative assessment of histological and CT slices by pathologists revealed that PhC-μ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mu$$\\end{document}CT aids in classifying lesions by highlighting distinct tissue components and, notably, identifying tissue invasion. Reviewing a volume image allows pathologists to trace the entire lesion, identifying invasion sites that might be overlooked in individual or serial histological sections. Consequently, this proposed method could complement pathologists’ tools, potentially enhancing diagnoses by minimizing under-staging and reducing false negative results.

Case report– Periapical cemento-osseous dysplasia–CBCT findings

Case report– Periapical cemento-osseous dysplasia–CBCT findings

Synthesis of a novel thio-anthraquinone derivative-based tissue dye

In this study, a new dye, Neurange stain, was developed for histopathological examination of brain tissue using light microscopy. In addition, Neurange dye can be used in routine analyses and microscopic imaging of tissue sections. The synthesis of 1-(4-hydroxyphenylthio)anthracene-9,10-dione (3), a new thio-anthraquinone derivative used in the preparation of Neurange dye, began with the substitution reaction of 4-hydroxythiophenol (2) and 1-chloroanthraquinone (1) as starting materials.1 Neurange dye shows specific staining of white matter in brain tissue sections. It shows brown-orange staining in areas such as the optic nerve, the cortex in the brain tissue, and areas where axon bundles are located, and especially areas related to the myelin sheath. In conclusion, Neurange dye could be used to distinguish different brain areas using a light microscope.

Multi-Pass Laser Polishing of As-Built Directed Energy Deposition Surfaces

Abstract Laser polishing (LP) provides a fast and efficient way of remelting part surfaces manufactured by additive manufacturing to alter both their geometric as well as physical properties. Depending on the laser parameters, remelted surfaces with different properties are achieved, with a majority exhibiting lower surface roughness compared to the original surface. In this study, a high-power continuous fiber laser is used to polish Inconel 718 (IN718) surfaces produced by depositing a single layer of clads on a steel substrate by the powder-blown directed energy deposition (DED) process. Polishing was performed under different sets of parameters, namely, laser power, beam diameter, feed rate or feed, hatch spacing, and the number of polishing passes. Their effects on the surface roughness profiles and the microstructural properties of the sample cross section were analyzed after one and two polishing passes. Optical microscopic images of the sample's cross sections show the presence of supersaturated γ phase particles, γ′+γ″ precipitates, Laves phases, and δ phase needles. The combined effect of high-temperature gradients and lower solidification rates in certain regions within the cross section results in undercooled regions and pseudo-heat treatment of unmelted regions close to the undercooled regions. These results are corroborated by indenting the various regions of the IN718 sample cross section with a pyramidal diamond indenter in the form of a grid, resulting in different micro-hardness values due to different densities of precipitate and phase transformed δ particles.

Numerical investigation of fluid flow behavior in steel cord with lattice Boltzmann methodology: The impacts of microstructure and loading force.

Steel cord materials were found to have internal porous microstructures and complex fluid flow properties. However, current studies have rarely reported the transport behavior of steel cord materials from a microscopic viewpoint. The computed tomography (CT) scanning technology and lattice Boltzmann method (LBM) were used in this study to reconstruct and compare the real three-dimensional (3D) pore structures and fluid flow in the original and tensile (by loading 800 N force) steel cord samples. The pore-scale LBM results showed that fluid velocities increased as displacement differential pressure increased in both the original and tensile steel cord samples, but with two different critical values of 3.3273 Pa and 2.6122 Pa, respectively. The original steel cord sample had higher maximal and average seepage velocities at the 1/2 sections of 3D construction images than the tensile steel cord sample. These phenomena should be attributed to the fact that when the original steel cord sample was stretched, its porosity decreased, pore radius increased, flow channel connectivity improved, and thus flow velocity increased. Moreover, when the internal porosity of tensile steel cord sample was increased by 1 time, lead the maximum velocity to increase by 1.52 times, and the average velocity was increased by 1.66 times. Furthermore, when the density range was determined to be 0-38, the pore phase showed the best consistency with the segmentation area. Depending on the Zou-He Boundary and Regularized Boundary, the relative error of simulated average velocities was only 0.2602 percent.

Ultrastructural features of primary cancer and its metastases

Mortality from metastatic lesions accounts for a significant proportion of oncological practice, and the issues of tumor chemoresistance and micrometastasis formation with the development of early recurrence are also important, which requires research and solution of these problems. Methods: The study used sectional material from the Pathology Department for ultrastructural examination of primary tumors and metastases, employing fixation, embedding, sectioning, staining, and electron microscopy imaging techniques.

Experiments on image data augmentation techniques for geological rock type classification with convolutional neural networks

The integration of image analysis through deep learning (DL) into rock classification represents a significant leap forward in geological research. While traditional methods remain invaluable for their expertise and historical context, DL offers a powerful complement by enhancing the speed, objectivity, and precision of the classification process. This research explores the significance of image data augmentation techniques in optimizing the performance of convolutional neural networks (CNNs) for geological image analysis, particularly in the classification of igneous, metamorphic, and sedimentary rock types from rock thin section (RTS) images. This study primarily focuses on classic image augmentation techniques and evaluates their impact on model accuracy and precision. Results demonstrate that augmentation techniques like Equalize significantly enhance the model's classification capabilities, achieving an F1-Score of 0.9869 for igneous rocks, 0.9884 for metamorphic rocks, and 0.9929 for sedimentary rocks, representing improvements compared to the baseline original results. Moreover, the weighted average F1-Score across all classes and techniques is 0.9886, indicating an enhancement. Conversely, methods like Distort lead to decreased accuracy and F1-Score, with an F1-Score of 0.949 for igneous rocks, 0.954 for metamorphic rocks, and 0.9416 for sedimentary rocks, exacerbating the performance compared to the baseline. The study underscores the practicality of image data augmentation in geological image classification and advocates for the adoption of DL methods in this domain for automation and improved results. The findings of this study can benefit various fields, including remote sensing, mineral exploration, and environmental monitoring, by enhancing the accuracy of geological image analysis both for scientific research and industrial applications.

New Scanographic Index for the Detection of Frailty in Patients with Cirrhosis with a Prognostic Impact.

Frailty is linked to an increased incidence of hepatic decompensation and mortality in cirrhosis. The aim of our study was to identify a novel scanographic score that predicts frailty and its impact in cirrhosis. This study included 51 patients with cirrhosis. We used the frailty scale risk assessment score to identify frail patients. The density and area of different muscles at L3 level were analyzed on computed tomography (CT) sections. The L3 skeletal muscle area adjusted to height and density ratio (L3-SMDHR) was defined as L3 muscle wall*height/density. The L3-SMHDR is significantly higher in frail patients and in patients with Child B/C scores. Frailty was correlated with L3-SMHDR. Frailty and L3- SMHDR were correlated with liver-related events (LRE). We set the most appropriate cut-offs of L3-SMHDR for both sensitivity and specificity by using the ROC: 5.4 for males and 4.7 for females. The AUROC score was 0.784 for male and 0.975 for female patients. The Kappa score between frailty and L3-SMHDR was 0.752, with a percentage of agreement of 87.5%, showing a substantial agreement. This ratio with the divided categories has a sensitivity of 100%, a specificity of 76%, a positive predictive value of 79.3% and a negative predictive value of 100%. Patients with high L3-SMHDR have significantly lower survival time and a higher incidence of LRE. The L3-SMHDR is a new index for identifying frailty in cirrhosis by using measurable and reproducible variables. It can be used as a prognostic factor for frailty in patients with cirrhosis.

APPLICATION OF ELECTRICAL RESISTIVITY METHOD FOR SAFETY EVALUATION OF ASEJIRE DAM IBADAN, SOUTHWESTERN NIGERIA

Dam construction provides economic importance to the environs through, water supply and flood control. Post-construction investigation is however necessary for maintenance stability to avoid irreversible environmental changes. In view of this, horizontal resistivity profiling and vertical electrical sounding (VES) were conducted along the embankments and the downstream of Asejire dam to determine its integrity. The methods used were horizontal resistivity profiling and vertical electrical soundings conducted along the embankments and the downstream. Thirty-one VES and Dipole-Dipole Profiling were occupied along the embankments and downstream using Resistivity meter at 20 m intervals for both the VES and Dipole-Dipole. The Dipole-Dipole data were inverted into 2-D Resistivity Images using DIPPRO™ 4.0 Inversion Software while the VES data were quantitatively interpreted using the partial curve matching technique and Winresist 1.0 Version Software. Results of dipole-dipole image and geo-electric section identified three geo-electric layers; comprising topsoil presumably clayey sand and laterites with resistivity and thickness between 59-760m and 0.7-5.2m respectively. The second layer is weathered layer attributed with clay/clayey sand having resistivity and thickness 18-766m and 3.1-36.7 m. The third layer suspected to be fresh bedrock with resistivity range 121-3672m and 18-766 m thick. The Dipole-Dipole results displayed resistivity less than 500m in the first layer with structural evidence of discontinuous observables, but the underlying sequences displayed no indicative of structural weakness. This significant features play a major role in seepage processes from the dam, therefore lithological composition obtained from these results shows the dam has a good integrity.

Subregion preference in the long-range connectome of pyramidal neurons in the medial prefrontal cortex

BackgroundThe medial prefrontal cortex (mPFC) is involved in complex functions containing multiple types of neurons in distinct subregions with preferential roles. The pyramidal neurons had wide-range projections to cortical and subcortical regions with subregional preferences. Using a combination of viral tracing and fluorescence micro-optical sectioning tomography (fMOST) in transgenic mice, we systematically dissected the whole-brain connectomes of intratelencephalic (IT) and pyramidal tract (PT) neurons in four mPFC subregions.ResultsIT and PT neurons of the same subregion projected to different target areas while receiving inputs from similar upstream regions with quantitative differences. IT and PT neurons all project to the amygdala and basal forebrain, but their axons target different subregions. Compared to subregions in the prelimbic area (PL) which have more connections with sensorimotor-related regions, the infralimbic area (ILA) has stronger connections with limbic regions. The connection pattern of the mPFC subregions along the anterior–posterior axis showed a corresponding topological pattern with the isocortex and amygdala but an opposite orientation correspondence with the thalamus.ConclusionsBy using transgenic mice and fMOST imaging, we obtained the subregional preference whole-brain connectomes of IT and pyramidal tract PT neurons in the mPFC four subregions. These results provide a comprehensive resource for directing research into the complex functions of the mPFC by offering anatomical dissections of the different subregions.

Machine learning-based wood anatomy identification: towards anatomical feature recognition

Summary Computer vision-based wood identification has been successfully applied to recognize tree species using digital images of wood sections or surfaces. However, this image-to-species approach can only recognize a limited number of species due to two main reasons: 1) the lack of a good reference database requiring high-quality standardized images from multiple individuals of hundreds or even thousands of traded timber species, and 2) species not included in the reference database cannot be identified without expert knowledge. Another bottleneck is that the feature extraction process used by these species recognition approaches is a black box, thereby creating a discrepancy between machine learning features and wood anatomical features. This discrepancy prevents wood anatomists from understanding how these machine-learning algorithms work. Here, we survey currently existing methods used in feature extraction, classification, and deep learning methods applied in wood identification along with their pitfalls and opportunities. As an example of how the field could move forward, we launch the idea of building an image-to-features-to-species identification approach based on microscopic wood images as well as text files comprising wood anatomical descriptions. If we can manage machine learning-based algorithms to recognize the main wood anatomical traits that experts use to identify species in a (semi-)automated way, this would boost wood identification in two ways: (1) extensive reference databases for each species would become less crucial as the databases are ordered at the trait level, (2) timber identification would become more feasible for species that have not yet been included in the reference database as long as wood anatomical descriptions are available.

Preliminary study on diagnosis of gallbladder neoplastic polyps based on contrast-enhanced ultrasound and grey scale ultrasound radiomics.

Neoplastic gallbladder polyps (GPs), including adenomas and adenocarcinomas, are considered absolute indications for surgery; however, the distinction of neoplastic from non-neoplastic GPs on imaging is often challenging. This study thereby aimed to develop a CEUS radiomics nomogram, and evaluate the role of a combined grey-scale ultrasound and CEUS model for the prediction and diagnosis of neoplastic GPs. Patients with GPs of ≥ 1cm who underwent CEUS between January 2017 and May 2022 were retrospectively enrolled. Grey-scale ultrasound and arterial phase CEUS images of the largest section of the GPs were used for radiomics feature extraction. Features with good reproducibility in terms of intraclass correlation coefficient were selected. Grey-scale ultrasound and CEUS Rad-score models were first constructed using the Mann-Whitney U and LASSO regression test, and were subsequently included in the multivariable logistic regression analysis as independent factors for construction of the combined model. A total of 229 patients were included in our study. Among them, 118 cholesterol polyps, 68 adenomas, 33 adenocarcinomas, 6 adenomyomatoses, and 4 inflammatory polyps were recorded. A total of 851 features were extracted from each patient. Following screening, 21 and 15 features were retained in the grey-scale and CEUS models, respectively. The combined model demonstrated AUCs of 0.88 (95% CI: 0.83 - 0.93) and 0.84 (95% CI: 0.74 - 0.93) in the training and testing set, respectively. When applied to the whole dataset, the combined model detected 111 of the 128 non-neoplastic GPs, decreasing the resection rate of non-neoplastic GPs to 13.3%. Our proposed combined model based on grey-scale ultrasound and CEUS radiomics features carries the potential as a non-invasive, radiation-free, and reproducible tool for the prediction and identification of neoplastic GPs. Our model may not only guide the treatment selection for GPs, but may also reduce the surgical burden of such patients.

An improved corner dealiasing and recognition algorithm for 2D Wadell roundness computation

This paper optimizes the 2D Wadell roundness calculation of particles based on digital image processing methods. An algorithm for grouping corner key points is proposed to distinguish each independent corner. Additionally, the cyclic midpoint filtering method is introduced for corner dealiasing, aiming to mitigate aliasing issues effectively. The relationships between the number of corner pixels (m), the central angle of the corner (α) and the parameter of the dealiasing degree (n) are established. The Krumbein chart and a sandstone thin section image were used as examples to calculate the 2D Wadell roundness. A set of regular shapes is calculated, and the error of this method is discussed. When α ≥ 30°, the maximum error of Wadell roundness for regular shapes is 5.21%; when 12° ≤ α < 30°, the maximum error increases. By applying interpolation to increase the corner pixels to the minimum number (m0) within the allowable range of error, based on the α-m0 relational expression obtained in this study, the error of the corner circle can be minimized. The results indicate that as the value of m increases, the optimal range interval for n also widens. Additionally, a higher value of α leads to a lower dependence on m. The study's results can be applied to dealiasing and shape analysis of complex closed contours.

Log cross section quality metrics: Assessing the usability of roundwood image data for roundwood tracking

The proof of origin of roundwood is becoming increasingly important. As part of the digitization of the forest-based sector and to combat illegal logging, there is a growing interest in tracking wood logs individually. There are several previous publications on biometric wood log tracking based on log image data. A major problem for wood log tracking is the often poor visibility of discriminative features in log ends, such as the annual ring pattern, which makes it very difficult to track such logs. In this work we propose a method that quantifies the usability of image data for the purpose of roundwood tracking. There are no previous publications on this topic. More specifically, we propose a quality map that assesses the usability of different regions of the log cross section and a global quality metric that assesses the quality of entire images. We will show that the local and global quality metrics reliably assess the quality of log cross section images. Furthermore, we will show that the quality map can be used to improve the results of deep learning based log recognition systems. By combining the image data with the local quality map, the roundwood tracking system gets additional information about the usability of the different regions of the log cross section for roundwood tracking, which leads to improvements in most of the results.

Using machine learning for chemical-free histological tissue staining

ABSTRACT Hematoxylin and eosin staining can be hazardous, expensive, and prone to error and variability. To circumvent these issues, artificial intelligence/machine learning models such as generative adversarial networks (GANs), are being used to ‘virtually’ stain unstained tissue images indistinguishable from chemically stained tissue. Frameworks such as deep convolutional GANs (DCGAN) and conditional GANs (CGANs) have successfully generated highly reproducible ‘stained’ images. However, their utility may be limited by requiring registered, paired images which can be difficult to obtain. To avoid these dataset requirements, we attempted to use an unsupervised CycleGAN pix2pix model(5,6) to turn unpaired, unstained bright-field images into pathologist-approved digitally ‘stained’ images. Using formalin-fixed-paraffin-embedded liver samples, 5µm section images (20x) were obtained before and after staining to create “stained” an “unstained” datasets. Model implementation was conducted using Ubuntu 20.04.4 LTS, 32 GB RAM, Intel Core i7-9750 CPU @2.6 GHz, Nvidia GeForce RTX 2070 Mobile, Python 3.7.11 and Tensorflow 2.9.1. The CycleGAN framework utilized a u-net-based generator and discriminator from pix2pix, a CGAN. The CycleGAN used a modified loss function, cycle consistent loss that assumed unpaired images, so loss was measured twice. To our knowledge, this is the first documented application of this architecture using unpaired bright-field images. Results and suggested improvements are discussed.

Identification of ultrastructural details of the astrocyte process system in neural tissue of the brain using correlative scanning probe and transmission electron microscopy

Nanoscale morphological features of branched processes of glial cells may be of decisive importance for neuron-astrocytic interactions in health and disease. The paper presents the results of a correlation analysis of images of thin processes of astrocytes in the nervous tissue of the mouse brain, obtained by scanning probe microscopy and transmission electron microscopy with high spatial resolution. Samples were prepared and imaged using a unique hardware combination of ultramicrotomy and scanning probe microscopy. It was shown that the images identified details of astrocytes with a thickness of the order of tens of nanometers, which can be used in the future to reconstruct the three-dimensional structure of astrocytic processes by integrating a series of sequential images of ultrathin sections of nervous tissue.

Assess the Effectiveness of Multichannel Analysis of Surface Waves Method in Mapping Ancient Structures in Ultrashallow Aquatic Environments: The Case of Agioi Theodoroi, Greece

ABSTRACTThe present geophysical research aims to evaluate the applicability of multichannel analysis of surface waves (MASW) on mapping ultrashallow underwater ancient masonry remnants. The work presents the analysis from a single seismic line using MASW and seismic refraction tomography (SRT) methods and its corresponding electrical resistivity tomography (ERT) section surveyed at the submerged prehistoric site of Agioi Theodoroi area located 10 km eastern of Heraklion, Crete, Greece. The 2D MASW velocity model exhibits significant correspondence with the resistivity structure extracted from the ERT data, showing lateral S‐wave velocity (Vs) variations at the positions where the high resistivity anomalies exist. The analysis of synthetic seismic data calculated from a respective model reproduced a comparable S‐wave velocity pseudo‐section with the real data. However, the investigated targets (submerged buried masonry) appear shallower and wider in MASW sections than in the real world and the corresponding synthetic models, due to insufficient vertical and horizontal resolution of this method. Surface waves travelling through the seafloor sediments (Scholte‐waves) demonstrate very low velocity values. This makes them suitable for the detection of shallow and relatively large (&gt; 0.5 m) underwater manmade structures, providing the enhancement of MASW method resolution, by utilizing a high frequency (&gt; 100 Hz) seismic source, recording short Scholte wavelengths (≤ 1 m) and using shorter (≤ 0.5 m) receiver spacing and array length. Consequently, the results of this work demonstrate the potential in employing conventional seismic techniques in the delineation of underwater antiquities and the revealing of the cultural dynamics in very shallow off‐shore archaeological sites.

Direct 3D Imaging through Spatial Coherence of Light

AbstractWide‐field imaging is widely adopted due to its fast acquisition, cost‐effectiveness, and ease of use. Its extension to direct volumetric applications, however, is burdened by the trade‐off between resolution and depth of field (DOF), dictated by the numerical aperture of the system. It is demonstrated that such trade‐off is not intrinsic to wide‐field imaging, but stems from the spatial incoherence of light: images obtained through spatially coherent illumination are shown to have resolution and DOF independent of the numerical aperture. This fundamental discovery enables to demonstrate an optimal combination of coherent resolution‐DOF enhancement and incoherent tomographic sectioning for scanning‐free, wide‐field 3D microscopy on a multicolor histological section.