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Artykuły w czasopismach na temat „Segmentation des pores”

Autor: Grafiati
Data publikacji: 7 września 2024
Data aktualizacji: 31 lipca 2025

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1

Sintorn, Ida-Maria, Stina Svensson, Maria Axelsson, and Gunilla Borgefors. "Segmentation of individual pores in 3D paper images." Nordic Pulp & Paper Research Journal 20, no. 3 (2005): 316–19. http://dx.doi.org/10.3183/npprj-2005-20-03-p316-319.

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Bauer, Benjamin, Xiaohao Cai, Stephan Peth, Katja Schladitz, and Gabriele Steidl. "Variational-based segmentation of bio-pores in tomographic images." Computers & Geosciences 98 (January 2017): 1–8. http://dx.doi.org/10.1016/j.cageo.2016.09.013.

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Liu, Lei, Qiaoling Han, Yue Zhao, and Yandong Zhao. "A Novel Method Combining U-Net with LSTM for Three-Dimensional Soil Pore Segmentation Based on Computed Tomography Images." Applied Sciences 14, no. 8 (2024): 3352. http://dx.doi.org/10.3390/app14083352.

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The non-destructive study of soil micromorphology via computed tomography (CT) imaging has yielded significant insights into the three-dimensional configuration of soil pores. Precise pore analysis is contingent on the accurate transformation of CT images into binary image representations. Notably, segmentation of 2D CT images frequently harbors inaccuracies. This paper introduces a novel three-dimensional pore segmentation method, BDULSTM, which integrates U-Net with convolutional long short-term memory (CLSTM) networks to harness sequence data from CT images and enhance the precision of pore
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4

Yosifov, Miroslav, Patrick Weinberger, Bernhard Plank, et al. "Segmentation of pores in carbon fiber reinforced polymers using the U-Net convolutional neural network." Acta Polytechnica CTU Proceedings 42 (October 12, 2023): 87–93. http://dx.doi.org/10.14311/app.2023.42.0087.

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This study demonstrates the utilization of deep learning techniques for binary semantic segmentation of pores in carbon fiber reinforced polymers (CFRP) using X-ray computed tomography (XCT) datasets. The proposed workflow is designed to generate efficient segmentation models with reasonable execution time, applicable even for users using consumer-grade GPU systems. First, U-Net, a convolutional neural network, is modified to handle the segmentation of XCT datasets. In the second step, suitable hyperparameters are determined through a parameter analysis (hyperparameter tuning), and the paramet
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5

Tomažinčič, Dejan, Žiga Virk, Peter Marijan Kink, Gregor Jerše, and Jernej Klemenc. "Predicting the Fatigue Life of an AlSi9Cu3 Porous Alloy Using a Vector-Segmentation Technique for a Geometric Parameterisation of the Macro Pores." Metals 11, no. 1 (2020): 72. http://dx.doi.org/10.3390/met11010072.

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Most of the published research work related to the fatigue life of porous, high-pressure, die-cast structures is limited to a consideration of individual isolated pores. The focus of this article is on calculating the fatigue life of high-pressure, die-cast, AlSi9Cu3 parts with many clustered macro pores. The core of the presented methodology is a geometric parameterisation of the pores using a vector-segmentation technique. The input for the vector segmentation is a μ-CT scan of the porous material. After the pores are localised, they are parameterised as 3D ellipsoids with the corresponding
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6

Ng, Hwee Ping, Qijian Chan, Zheng Jie Tan, Ronnie Ssebaggala, and Joseph John Lifton. "Segmenting spatter particles on additively manufactured surfaces using deep learning." Surface Topography: Metrology and Properties 13, no. 1 (2025): 015006. https://doi.org/10.1088/2051-672x/ada6e1.

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Abstract Metal additively manufactured (AM) surfaces do not exhibit the same surface features as machined surfaces. Rather than cutting marks, the additive surface may display surface features such as spatter particles, weld tracks, cracks, and surface breaking pores. These features are not well described by surface height parameters that were developed for machined surfaces. Therefore, an AM specific surface characterisation approach is required; feature based surface characterisation is a promising approach, but it requires surface features to be manually segmented which is a subjective proc
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7

Tomina, E., K. Zhuzhukin, A. Dmitrenkov, et al. "Study of the quality of impregnation and structural features of birch wood using the method of micro-X-ray computed tomography." Forestry Engineering Journal 14, no. 4 (2025): 172–86. https://doi.org/10.34220/issn.2222-7962/2024.4/12.

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Quality control of the internal structure of wood is an urgent task from both scientific and practical points of view. Existing control methods mainly imply a destructive approach associated with the destruction of a part of the product, which in some cases is impossible. In this study, the morphological features of the void space of wood were studied with an assessment of open porosity, pore size distribution, as well as a separate analysis of the void space with spatial determination and assessment of the sizes of pores filled with impregnation and empty pores using the method of micro-X-ray
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8

Tong, Tong, Yan Cai, Da Wei Sun, and Peng Liu. "Automatic Segmentation of Pores in Weld Images Based on Transition Region Extraction." Applied Mechanics and Materials 217-219 (November 2012): 1964–67. http://dx.doi.org/10.4028/www.scientific.net/amm.217-219.1964.

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In allusion to the complex images of weld defects, weak contrast between the target and the background, a new segmentation method based on gray level difference transition region extraction is proposed. The paper analyzes the characteristic of weld defects, and then low-pass filtering and contrast enhanced are used to enhance the clarity. Finally, we extract the transition region and confirm a threshold for defects segmentation. The experimental results show that the method can extract the transition region more accurate, and segment the image much better in complex environment.
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9

Zhao, Keying, and Zhanghua Zhang. "NMR and SEM fractal dimensions explore shale pore structure taking the Upper Paleozoic shale in Ordos Basin as an example." PLOS One 20, no. 5 (2025): e0323968. https://doi.org/10.1371/journal.pone.0323968.

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In this paper, the fractal dimension is calculated by extracting pore parameters from SEM images and NMR experimental data, the pore structure heterogeneity in plane and space is comprehensively discussed, and the relationship between the fractal dimension and shale composition and physical parameters is discussed, providing new ideas for the study of shale reservoirs heterogeneity. Fractal dimension analysis of SEM images reveals that the shale pores of the Shanxi Formation can be divided into organic pores, inter-granular pores and micro-fractures. The average diameter of nano-scale pores is
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10

Yoon, Huisu, Semin Kim, Jongha Lee, and Sangwook Yoo. "Deep-Learning-Based Morphological Feature Segmentation for Facial Skin Image Analysis." Diagnostics 13, no. 11 (2023): 1894. http://dx.doi.org/10.3390/diagnostics13111894.

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Facial skin analysis has attracted considerable attention in the skin health domain. The results of facial skin analysis can be used to provide skin care and cosmetic recommendations in aesthetic dermatology. Because of the existence of several skin features, grouping similar features and processing them together can improve skin analysis. In this study, a deep-learning-based method of simultaneous segmentation of wrinkles and pores is proposed. Unlike color-based skin analysis, this method is based on the analysis of the morphological structures of the skin. Although multiclass segmentation i
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11

Song, Wenlong, Junyu Li, Kexin Li, Jingxu Chen, and Jianping Huang. "An Automatic Method for Stomatal Pore Detection and Measurement in Microscope Images of Plant Leaf Based on a Convolutional Neural Network Model." Forests 11, no. 9 (2020): 954. http://dx.doi.org/10.3390/f11090954.

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Stomata are microscopic pores on the plant epidermis that regulate the water content and CO2 levels in leaves. Thus, they play an important role in plant growth and development. Currently, most of the common methods for the measurement of pore anatomy parameters involve manual measurement or semi-automatic analysis technology, which makes it difficult to achieve high-throughput and automated processing. This paper presents a method for the automatic segmentation and parameter calculation of stomatal pores in microscope images of plant leaves based on deep convolutional neural networks. The pro
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12

Soboleva, N. N., and A. N. Mushnikov. "Determination of the volume fraction of primary carbides in the microstructure of composite coatings using semantic segmentation." Frontier materials & technologies, no. 3 (2023): 95–102. http://dx.doi.org/10.18323/2782-4039-2023-3-65-9.

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In the process of formation of composite coatings, partial dissolution of hardening particles (most often carbides) in the matrix is possible; therefore, in some cases, the material creation mode is chosen taking into account the volume fraction of primary carbides not dissolved during coating deposition. The methods currently widely used for calculating the volume fraction of carbides in the structure of composite coatings (manual point method and programs implementing classical computer vision methods) have limitations in terms of the possibility of automation. It is expected that performing
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13

Wen, Hao, Chang Huang, and Shengmin Guo. "The Application of Convolutional Neural Networks (CNNs) to Recognize Defects in 3D-Printed Parts." Materials 14, no. 10 (2021): 2575. http://dx.doi.org/10.3390/ma14102575.

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Cracks and pores are two common defects in metallic additive manufacturing (AM) parts. In this paper, deep learning-based image analysis is performed for defect (cracks and pores) classification/detection based on SEM images of metallic AM parts. Three different levels of complexities, namely, defect classification, defect detection and defect image segmentation, are successfully achieved using a simple CNN model, the YOLOv4 model and the Detectron2 object detection library, respectively. The tuned CNN model can classify any single defect as either a crack or pore at almost 100% accuracy. The
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14

Lingnau, Lars A., Johannes Heermant, Johannes L. Otto, et al. "Separation of Damage Mechanisms in Full Forward Rod Extruded Case-Hardening Steel 16MnCrS5 Using 3D Image Segmentation." Materials 17, no. 12 (2024): 3023. http://dx.doi.org/10.3390/ma17123023.

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In general, formed components are lightweight as well as highly economic and resource efficient. However, forming-induced ductile damage, which particularly affects the formation and growth of pores, has not been considered in the design of components so far. Therefore, an evaluation of forming-induced ductile damage would enable an improved design and take better advantage of the lightweight nature as it affects the static and dynamic mechanical material properties. To quantify the amount, morphology and distribution of the pores, advanced scanning electron microscopy (SEM) methods such as sc
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15

LIN, WEI, XIZHE LI, ZHENGMING YANG, et al. "A NEW IMPROVED THRESHOLD SEGMENTATION METHOD FOR SCANNING IMAGES OF RESERVOIR ROCKS CONSIDERING PORE FRACTAL CHARACTERISTICS." Fractals 26, no. 02 (2018): 1840003. http://dx.doi.org/10.1142/s0218348x18400030.

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Based on the basic principle of the porosity method in image segmentation, considering the relationship between the porosity of the rocks and the fractal characteristics of the pore structures, a new improved image segmentation method was proposed, which uses the calculated porosity of the core images as a constraint to obtain the best threshold. The results of comparative analysis show that the porosity method can best segment images theoretically, but the actual segmentation effect is deviated from the real situation. Due to the existence of heterogeneity and isolated pores of cores, the por
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16

Devi, M. Shyamala, A. N. Sruthi, and P. Balamurugan. "Artificial neural network classification-based skin cancer detection." International Journal of Engineering & Technology 7, no. 1.1 (2017): 591. http://dx.doi.org/10.14419/ijet.v7i1.1.10364.

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At present, skin cancers are extremely the most severe and life-threatening kind of cancer. The majority of the pores and skin cancers are completely remediable at premature periods. Therefore, a premature recognition of pores and skin cancer can effectively protect the patients. Due to the progress of modern technology, premature recognition is very easy to identify. It is not extremely complicated to discover the affected pores and skin cancers with the exploitation of Artificial Neural Network (ANN). The treatment procedure exploits image processing strategies and Artificial Intelligence. I
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17

Grigorchenko, S. A., and V. I. Kapustin. "Improving the Efficiency of Defect Image Identification During Computer Decoding of Digital Radiographic Images of Welded Joints of Hazardous Production Facilities." Defektoskopiâ, no. 12 (December 18, 2024): 59–68. https://doi.org/10.31857/s0130308224120056.

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This article is devoted to improving the efficiency of flaw image identification during computer decoding of digital radiographic images. The paper studies the problem of segmentation of flaw images. Models of segmentation of flaw images on a radiographic image are studied for both manual and computer decoding. The difference between algorithms for searching and identifying groups, clusters, chains of pores, slag and metal inclusions from manual decoding of images is shown. Algorithms for the search and identification of flaws for use in digital radiography complexes have been developed and ex
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18

Van Eyndhoven, G., M. Kurttepeli, C. J. Van Oers, et al. "Pore REconstruction and Segmentation (PORES) method for improved porosity quantification of nanoporous materials." Ultramicroscopy 148 (January 2015): 10–19. http://dx.doi.org/10.1016/j.ultramic.2014.08.008.

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Braakman, Sietse T., A. Thomas Read, Darren W. H. Chan, C. Ross Ethier, and Darryl R. Overby. "Colocalization of outflow segmentation and pores along the inner wall of Schlemm's canal." Experimental Eye Research 130 (January 2015): 87–96. http://dx.doi.org/10.1016/j.exer.2014.11.008.

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Tang, Xin, Ruiyu He, Biao Wang, Yuerong Zhou та Hong Yin. "Intelligent Identification and Quantitative Characterization of Pores in Shale SEM Images Based on Pore-Net Deep-Learning Network Model". Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description 65, № 2 (2024): 233–45. http://dx.doi.org/10.30632/pjv65n2-2024a6.

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Among the various shale reservoir evaluation methods, the scanning electron microscope (SEM) image method is widely used. Its image can intuitively reflect the development stage of a shale reservoir and is often used for the qualitative characterization of shale pores. However, manual image processing is inefficient and cannot quantitatively characterize pores. The semantic segmentation method of deep learning greatly improves the efficiency of image analysis and can calculate the face rate of shale SEM images to achieve quantitative characterization. In this paper, the high-maturity shale of
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21

P., S. Aithal, and Prasad K. Krishna. "Fingerprint Image Segmentation: A Review of State of the Art Techniques." International Journal of Management, Technology, and Social Sciences (IJMTS) 2, no. 2 (2017): 28–39. https://doi.org/10.5281/zenodo.848191.

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In Automatic Fingerprint Identification System (AFIS), pre-processing of the image is a crucial process in deciding the quality and performance of the system. Pre-processing is consists many stages as Segmentation, Enhancement, Binarisation, and Thinning. In this segmentation is one of the steps of pre-processing which differentiate foreground and background region of fingerprint images. Segmentation is the separation of the fingerprint region or extraction of the presence of ridges from the background of the initial image. Segmentation is necessary because it constructs the region of interest
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22

Massey, C. E., J. C. Miers, D. G. Moore, P. E. Specht, and B. A. Branch. "Defect And Damage Characterization Of Additively Manufactured Titanium Alloy Ti-5553 Using Traditional Computed Tomography Volume Segmentation And Machine Learning Algorithms." Materials Evaluation 83, no. 1 (2025): 40–49. https://doi.org/10.32548/2025.me-04478.

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The mechanical response of a component is affected by defects, such as porosity, arising from the laser powder bed fusion (LPBF) fabrication process. Thus, it is important to develop accurate and efficient inspection methods for identifying porosity. In this work, porosity identified in an X-ray computed tomography (XCT) volume of a Ti-5553 coupon was compared to pores identified in a serial sectioned volume that represented the ground truth. The porosity of the XCT scan was identified using contrast-based, ISO-based, and machine learning (ML) methods for segmentation. Large inherent porosity
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Báez, Francisco, Álvaro A. Camargo, and Gustavo D. A. Gastal. "Ultrastructural Imaging Analysis of the Zona Pellucida Surface in Bovine Oocytes." Microscopy and Microanalysis 25, no. 4 (2019): 1032–36. http://dx.doi.org/10.1017/s1431927619000692.

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AbstractThe aims of the present study were to: (i) evaluate the ultrastructural differences in the zona pellucida (ZP) surface between immature and mature bovine oocytes, and (ii) describe a new objective technique to measure the pores in the outer ZP. Intact cumulus–oocyte complexes (COCs) obtained from a local abattoir were immediately fixed (immature group) or submitted to in vitro maturation (IVM) at 38.5 °C for 24 h in a humidified atmosphere of 5% CO2 in air (mature group). Oocytes from both groups were morphologically evaluated via Scanning Electron Microscopy (SEM) and the images were
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24

Bondarev, A. V., E. T. Zhilyakova, N. B. Demina, and V. Y. Novikov. "Study of Morphology of Sorption Substances." Drug development & registration 8, no. 2 (2019): 33–37. http://dx.doi.org/10.33380/2305-2066-2019-8-2-33-37.

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Introduction. Substances with sorption properties can be used to create transport drug systems, in which the main mechanism of binding, transport and release of the drug molecule is sorption. The sorbent in this case acts as a carrier of the drug molecule, followed by its delivery to the destination by desorption. One of the ways to study the processes of sorption-desorption in transport drug systems is the study of the morphology of the sorption substance. Therefore, the morphological analysis of sorption substances is important, including the size, shape, and spatial organization of their st
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Heylen, Rob, Aditi Thanki, Dries Verhees, et al. "3D total variation denoising in X-CT imaging applied to pore extraction in additively manufactured parts." Measurement Science and Technology 33, no. 4 (2022): 045602. http://dx.doi.org/10.1088/1361-6501/ac459a.

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Abstract X-ray computed tomography (X-CT) plays an important role in non-destructive quality inspection and process evaluation in metal additive manufacturing, as several types of defects such as keyhole and lack of fusion pores can be observed in these 3D images as local changes in material density. Segmentation of these defects often relies on threshold methods applied to the reconstructed attenuation values of the 3D image voxels. However, the segmentation accuracy is affected by unavoidable X-CT reconstruction features such as partial volume effects, voxel noise and imaging artefacts. Thes
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Suryaneta, Suryaneta, Angga Saputra Yasir, Wafiq Azizah Muhtar, Aida Febina Sholeha, Petrus Alvin Peter Ambarita, and Tri Noviantoro. "ANALYSIS OF SKIN CONDITIONS IN EARLY ADULT CONSUMERS USING A SKIN ANALYZER." Indonesian Journal of Cosmetics 2, no. 1 (2024): 35–46. https://doi.org/10.35472/ijcos.v2i1.1795.

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This study aimed to analyze the skin characteristics of early adult consumers using data collected from a skin analyzer and explore the implications for cosmetic product formulation. The research sample consisted of 73 participants, with the majority aged between 17 and 20 years. The measured skin parameters included moisture, pores, melanin, acne (acne), wrinkles, and sensitivity. Data were analyzed using descriptive statistics and consumer segmentation techniques. The findings revealed that the early adult consumers in the sample generally exhibited low skin moisture levels (56.2%), enlarged
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ZHU, QINGYONG, WEIBIN YANG, and HUAIZHONG YU. "STUDY ON THE PERMEABILITY OF RED SANDSTONE VIA IMAGE ENHANCEMENT." Fractals 25, no. 06 (2017): 1750055. http://dx.doi.org/10.1142/s0218348x17500554.

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Scanning electron microscopy (SEM) is of great importance for studying fractal permeability. In this work, we presented a new technique, by applying the high-order upwind compact difference schemes to solve the hyperbolic conservation laws, to enhance textural differences for accurate segmentation of the SEM images. From the enhanced SEM images, the channels and pores can be obtained by using the two-stage image segmentation. Combining with the box counting method, the key parameters for evaluation of the fractal permeability such as the tortuosity fractal dimension, the pore area fractal dime
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Hwang, Heesu, Dohyoung Kim, Yoonmi Nam, Jong-Ho Lee, and Jin-Ha Hwang. "Synergistic Application of Machine Learning to Microstructural Characterization on Electrode Composites of Solid Oxide Fuel Cells." ECS Transactions 111, no. 6 (2023): 445–51. http://dx.doi.org/10.1149/11106.0445ecst.

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Solid oxide fuel cells (SOFCs) have been recognized as one of the powerful next-generation energy conversion systems in association of the demanding green carbon technology. The electrochemical performance is crucially dependent on the intricate microstructures of porous electrodes, either cathodes or anodes. The composite electrodes should be analyzed in the sophisticated manner by characterizing the microstructural parameters. The current work combines electron microscopy with machine learning, more specifically semantic segmentation. The semantic segmentation was synergistically combined wi
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Fu, Yinkai, Yue Zhao, Yandong Zhao, and Qiaoling Han. "Semi-supervised segmentation of multi-scale soil pores based on a novel receptive field structure." Computers and Electronics in Agriculture 212 (September 2023): 108071. http://dx.doi.org/10.1016/j.compag.2023.108071.

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Suo, Limin, Zhaowei Wang, Hailong Liu, Likai Cui, Xianda Sun, and Xudong Qin. "Innovative Deep Learning Approaches for High-Precision Segmentation and Characterization of Sandstone Pore Structures in Reservoirs." Applied Sciences 14, no. 16 (2024): 7178. http://dx.doi.org/10.3390/app14167178.

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The detailed characterization of the pore structure in sandstone is pivotal for the assessment of reservoir properties and the efficiency of oil and gas exploration. Traditional fully supervised learning algorithms are limited in performance enhancement and require a substantial amount of accurately annotated data, which can be challenging to obtain. To address this, we introduce a semi-supervised framework with a U-Net backbone network. Our dataset was curated from 295 two-dimensional CT grayscale images, selected at intervals from nine 4 mm sandstone core samples. To augment the dataset, we
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Xia, Zhongyi, Boqi Wu, C. Y. Chan, Tianzhao Wu, Man Zhou, and Ling Bing Kong. "Deep-learning-based pyramid-transformer for localized porosity analysis of hot-press sintered ceramic paste." PLOS ONE 19, no. 9 (2024): e0306385. http://dx.doi.org/10.1371/journal.pone.0306385.

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Scanning Electron Microscope (SEM) is a crucial tool for studying microstructures of ceramic materials. However, the current practice heavily relies on manual efforts to extract porosity from SEM images. To address this issue, we propose PSTNet (Pyramid Segmentation Transformer Net) for grain and pore segmentation in SEM images, which merges multi-scale feature maps through operations like recombination and upsampling to predict and generate segmentation maps. These maps are used to predict the corresponding porosity at ceramic grain boundaries. To increase segmentation accuracy and minimize l
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Zhao, Xinli, Zhengming Yang, Xuewei Liu, Zhiyuan Wang, and Yutian Luo. "Analysis of pore throat characteristics of tight sandstone reservoirs." Open Geosciences 12, no. 1 (2020): 977–89. http://dx.doi.org/10.1515/geo-2020-0121.

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AbstractThe characterization of pore throat structure in tight reservoirs is the basis for the effective development of tight oil. In order to effectively characterize the pore -throat structure of tight sandstone in E Basin, China, this study used high-pressure mercury intrusion (HPMI) testing technology and thin section (TS) technology to jointly explore the characteristics of tight oil pore throat structure. The results of the TS test show that there are many types of pores in the tight sandstone, mainly the primary intergranular pores, dissolved pores, and microfractures. Based on the pore
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Zhao, Jiang Kun, Yu Zhu, and Jian Feng Yu. "Segmentation by Local Binary Fitting Active Contour Model for Activated Carbon Fibers Material Microscopic Images." Advanced Materials Research 811 (September 2013): 370–74. http://dx.doi.org/10.4028/www.scientific.net/amr.811.370.

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Many bubbles and pores are appeared on Activated Carbon Fibers (ACFs) material microscopic images. The morphology of ACFs surface image is complicated. Some widely used traditional methods are difficult to segment the object correctly. In this paper, an implicit active contour driven by local binary fitting energy is used to segment the objects for ACFs micro-images. This method is based on local image edge information to obtain optimal level set active contour model. Experimental results show that this active contour model is flexible for analyzing images with complex porous structure.
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Lu, Yangchun, Ting Lu, Yudong Lu, Bo Wang, Guanghao Zeng, and Xu Zhang. "The Study on Solving Large Pore Heat Transfer Simulation in Malan Loess Based on Volume Averaging Method Combined with CT Scan Images." Sustainability 15, no. 16 (2023): 12389. http://dx.doi.org/10.3390/su151612389.

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Malan loess is a wind-formed sediment in arid and semi-arid regions and is an important constituent of the Earth’s critical zone. Therefore, the study of the relationship between microstructure and heat transfer in Malan loess is of great significance for the in-depth understanding of the heat transfer mechanism and the accurate prediction of the heat transfer properties of intact loess. In order to quantitatively characterize the heat transfer processes in the two-phase medium of solid particles and gas pores in the intact loess, this study used modern computed tomography to CT scan the Malan
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Pan, Shen, and Mineichi Kudo. "Segmentation of pores in wood microscopic images based on mathematical morphology with a variable structuring element." Computers and Electronics in Agriculture 75, no. 2 (2011): 250–60. http://dx.doi.org/10.1016/j.compag.2010.11.010.

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Żak, Andrzej M., Anna Wieczorek, Agnieszka Chowaniec, and Łukasz Sadowski. "Segmentation of pores within concrete-epoxy interface using synchronous chemical composition mapping and backscattered electron imaging." Measurement 206 (January 2023): 112334. http://dx.doi.org/10.1016/j.measurement.2022.112334.

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37

Tkachev, Sergey, Natalia Chepelova, Gevorg Galechyan, et al. "Three-Dimensional Cell Culture Micro-CT Visualization within Collagen Scaffolds in an Aqueous Environment." Cells 13, no. 15 (2024): 1234. http://dx.doi.org/10.3390/cells13151234.

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Among all of the materials used in tissue engineering in order to develop bioequivalents, collagen shows to be the most promising due to its superb biocompatibility and biodegradability, thus becoming one of the most widely used materials for scaffold production. However, current imaging techniques of the cells within collagen scaffolds have several limitations, which lead to an urgent need for novel methods of visualization. In this work, we have obtained groups of collagen scaffolds and selected the contrasting agents in order to study pores and patterns of cell growth in a non-disruptive ma
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38

Fager, Andrew, Hiroshi Otomo, Rafael Salazar-Tio, et al. "Multi-scale Digital Rock: Application of a multi-scale multi-phase workflow to a Carbonate reservoir rock." E3S Web of Conferences 366 (2023): 01001. http://dx.doi.org/10.1051/e3sconf/202336601001.

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In some of the challenging digital rock applications the trade-off between model resolution and representative elemental volume is not captured in a single resolution model satisfying the minimum requirements for both aspects. In the wide range of lithofacies found in carbonate reservoir rocks, some facies fall in this category, where large pores, ooids or vugs, are connected by small scale porous structures that could have orders of magnitude smaller pores. In these cases a multi-scale digital rock approach is needed. We recently developed an extension to a digital rock workflow that includes
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39

Pramana, A. A., G. Riantomo, A. P. Oktaviani, I. Setiabudi, F. D. E. Latief, and M. A. Gibrata. "Digital Rock Physics Application in Determining The Porosity of Shale Rock." Journal of Physics: Conference Series 2243, no. 1 (2022): 012021. http://dx.doi.org/10.1088/1742-6596/2243/1/012021.

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Abstract This research is focusing on determining the porosity of shale rock using the Digital Rock Physics (DRP) method. The DRP method uses fiji software to process μCT-scan data of shale coreplug through segmentation and thresholding processes to determine the pores of the rock and then to determine the value of rock porosity. The purpose of this research is to be able to determine the value of rock porosity more quickly and to verify the DRP porosity result to that of laboratory test. The result shows that the porosity value obtained by the DRP method and laboratory test has a small differ
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Zhang, Hao, Hewen Liu, and Jinyong Bai. "Research on image recognition method of rock and soil porous media based on dithering algorithm." E3S Web of Conferences 283 (2021): 01025. http://dx.doi.org/10.1051/e3sconf/202128301025.

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Rock-soil mass is a kind of material with complex internal structure, and its macro-mechanical response and failure process are influenced by internal microscopic composition and structure. Based on the research results of digital image technology in quantitative aspects of internal structure of rock and soil, a method for segmentation of rock and soil pore images based on dithering algorithm and statistical method for multiple parameters of pores is proposed in this paper. The result of verification shows that the pore recognition method proposed in this paper is reliable, can obtain the pore
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Hu, Zhazha, Rui Zhang, Kai Zhu, et al. "Probing the Pore Structure of the Berea Sandstone by Using X-ray Micro-CT in Combination with ImageJ Software." Minerals 13, no. 3 (2023): 360. http://dx.doi.org/10.3390/min13030360.

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During diagenesis, the transformation of unconsolidated sediments into a sandstone is usually accompanied by compaction, water expulsion, cementation and dissolution, which fundamentally control the extent, connectivity and complexity of the pore structure in sandstone. As the pore structure is intimately related to fluid flow in porous media, it is of great importance to characterize the pore structure of a hydrocarbon-bearing sandstone in a comprehensive way. Although conventional petrophysical methods such as mercury injection porosimetry, low-pressure nitrogen or carbon dioxide adsorption
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Han, Yubo, and Ye Liu. "Intelligent Classification and Segmentation of Sandstone Thin Section Image Using a Semi-Supervised Framework and GL-SLIC." Minerals 14, no. 8 (2024): 799. http://dx.doi.org/10.3390/min14080799.

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This study presents the development and validation of a robust semi-supervised learning framework specifically designed for the automated segmentation and classification of sandstone thin section images from the Yanchang Formation in the Ordos Basin. Traditional geological image analysis methods encounter significant challenges due to the labor-intensive and error-prone nature of manual labeling, compounded by the diversity and complexity of rock thin sections. Our approach addresses these challenges by integrating the GL-SLIC algorithm, which combines Gabor filters and Local Binary Patterns f
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43

Scott, Sarah, Wei-Ying Chen, and Alexander Heifetz. "Multi-Task Learning of Scanning Electron Microscopy and Synthetic Thermal Tomography Images for Detection of Defects in Additively Manufactured Metals." Sensors 23, no. 20 (2023): 8462. http://dx.doi.org/10.3390/s23208462.

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One of the key challenges in laser powder bed fusion (LPBF) additive manufacturing of metals is the appearance of microscopic pores in 3D-printed metallic structures. Quality control in LPBF can be accomplished with non-destructive imaging of the actual 3D-printed structures. Thermal tomography (TT) is a promising non-contact, non-destructive imaging method, which allows for the visualization of subsurface defects in arbitrary-sized metallic structures. However, because imaging is based on heat diffusion, TT images suffer from blurring, which increases with depth. We have been investigating th
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Bondarev, Alexander, Elena Zhilyakova, Anastasia Malyutina, et al. "Structural features of mineral carriers of medicinal substances." BIO Web of Conferences 40 (2021): 03007. http://dx.doi.org/10.1051/bioconf/20214003007.

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The aim of the work is to investigation of the structural features of mineral carriers of medicinal substances. Tasks: conduct electron microscopy and study the structural features of mineral sorbents; develop a classification of sorption interaction. The materials are Smectite Dioctahedral (registration certificate N 015155/01, France), Kaolin (state standard 19608-84, Russia), Montmorillonite Clay (technical specifications 9296-001-62646221-2012, Russia). The methods are scanning electron microscopy on a FEI Quanta 600 microscope with a low vacuum mode and an LFD detector. Results. Electron
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Xavier, Matheus S., Sam Yang, Christophe Comte, Alireza Bab-Hadiashar, Neil Wilson, and Ivan Cole. "Nondestructive quantitative characterisation of material phases in metal additive manufacturing using multi-energy synchrotron X-rays microtomography." International Journal of Advanced Manufacturing Technology 106, no. 5-6 (2019): 1601–15. http://dx.doi.org/10.1007/s00170-019-04597-y.

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AbstractMetal additive manufacturing (MAM) has found emerging application in the aerospace, biomedical and defence industries. However, the lack of reproducibility and quality issues are regarded as the two main drawbacks to AM. Both of these aspects are affected by the distribution of defects (e.g. pores) in the AM part. Computed tomography (CT) allows the determination of defect sizes, shapes and locations, which are all important aspects for the mechanical properties of the final part. In this paper, data-constrained modelling (DCM) with multi-energy synchrotron X-rays is employed to charac
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Xiao, Xiaoling, Jiarui Zhang, Xinyu Li, Jing Zhang, and Xiang Zhang. "Study on Extraction Methods for Different Components in a Carbonate Digital Core." Mathematical Problems in Engineering 2020 (September 7, 2020): 1–6. http://dx.doi.org/10.1155/2020/8972494.

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It is difficult to carry out petrophysical experiments because of the serious damage caused to cores in the development of fractures and pores in carbonate reservoirs. The development of a three-dimensional digital core in carbonate reservoirs has become a hot topic in rock physics research. Compared with the three-dimensional digital core, including basic rock skeletons and pores in sandstone reservoirs, carbonate reservoirs also include secondary structures such as microfractures. The carbonate contains different components, and extracting these components is a very difficult problem. The re
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Honda, A., and Yu Lyashenko. "RESEARCH OF THE MORPHOLOGY OF THE CONTACT ZONE OF COPPER WELDED CONTACTS USING IMAGES SEGMENTATION OF STRUCTURAL ELEMENTS BASED ON WAVELET TRANSFORM." Cherkasy University Bulletin: Physical and Mathematical Sciences, no. 1 (2022): 23–32. https://doi.org/10.31651/2076-5851-2022-23-32.

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The article focuses on the analysis of the morphology of the contact zone of copper junctions using image texture segmentation algorithms and the OpenCV library. The article discusses the main approaches to the selection of interphase boundaries using the OpenCV graphics library and the use of the Gabor filter to select pore contours, detect defects and pores on interfaces, and establish contact zone phase ratios. The image processing procedure, based on Gabor filtering, was developed and tested. The phase areas at the interfaces of the diffusion zones of the Cu-Sn system were calculated for t
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48

Song, Meihui, Yue Zhao, Yandong Zhao, and Qiaoling Han. "ACFTransUNet: A new multi-category soil pores 3D segmentation model combining Transformer and CNN with concentrated-fusion attention." Computers and Electronics in Agriculture 225 (October 2024): 109312. http://dx.doi.org/10.1016/j.compag.2024.109312.

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Idowu, N. A. A., C. Nardi, H. Long, T. Varslot, and P. E. E. Øren. "Effects of Segmentation and Skeletonization Algorithms on Pore Networks and Predicted Multiphase-Transport Properties of Reservoir-Rock Samples." SPE Reservoir Evaluation & Engineering 17, no. 04 (2014): 473–83. http://dx.doi.org/10.2118/166030-pa.

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Summary Networks of large pores connected by narrower throats (pore networks) are essential inputs into network models that are routinely used to predict transport properties from digital rock images. Extracting pore networks from microcomputed-tomography (micro-CT) images of rocks involves a number of steps: filtering, segmentation, skeletonization, and others. Because of the amount of clay and its distribution, the segmentation of micro-CT images is not trivial, and different algorithms exist for achieving this. Similarly, several methods are available for skeletonizing the segmented images
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Nemati, Saber, Hamed Ghadimi, Xin Li, Leslie G. Butler, Hao Wen, and Shengmin Guo. "Automated Defect Analysis of Additively Fabricated Metallic Parts Using Deep Convolutional Neural Networks." Journal of Manufacturing and Materials Processing 6, no. 6 (2022): 141. http://dx.doi.org/10.3390/jmmp6060141.

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Laser powder bed fusion (LPBF)-based additive manufacturing (AM) has the flexibility in fabricating parts with complex geometries. However, using non-optimized processing parameters or using certain feedstock powders, internal defects (pores, cracks, etc.) may occur inside the parts. Having a thorough and statistical understanding of these defects can help researchers find the correlations between processing parameters/feedstock materials and possible internal defects. To establish a tool that can automatically detect defects in AM parts, in this research, X-ray CT images of Inconel 939 sample
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