scholarly journals Core-CT:  A MATLAB application for the quantitative analysis of sediment and coral cores from X-ray computed tomography (CT) 

2021 ◽  
Author(s):  
Yu Ting Yan ◽  
Stephen Chua ◽  
Thomas DeCarlo ◽  
Philipp Kempf ◽  
Kyle Morgan ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Linear Extension ◽  
Sediment Cores ◽  
Sedimentary Facies ◽  
Ct Number ◽  
Detailed Measurement ◽  
X Ray ◽  
3D Visualisation ◽  
Growth Bands ◽  
X Ray Computed

<div> <p>X-ray computed tomography (CT) is a non-destructive imaging technique that provides three-dimensional (3D) visualisation and high-resolution quantitative data in the form of CT numbers. CT numbers are derived as a function of the X-ray energy, effective atomic number and density of the sample. The sensitivity of the CT number to changes in material density allows it to successfully identify facies changes within sediment cores by detecting downcore shifts in sediment properties, and quantify skeletal linear extension rates and the volume of internal voids from biological erosion of coral cores. Here we present two algorithms to analyse CT scan images specific to geoscience research packaged within an open source MATLAB application (Core-CT). The first algorithm facilitates the computation of representative CT numbers from a user-defined region of interest to identify boundaries of density change (e.g. sedimentary facies, laminations, coral growth bands). The second algorithm enables the segmentation of regions with major density contrast (e.g. internal void space or biogenic material) and the geometric measurements of these irregularities. The versatility of Core-CT for geoscience applications is then demonstrated by utilising CT scans from a range of environmental settings comprising both sediment (Lake Huelde, Chile and Kallang River Basin, Singapore) and coral cores (Thuwal region of Red Sea, Saudi Arabia). Analysis of sediment cores show the capabilities of Core-CT to: 1) locate tsunami deposits from lacustrine sediments, 2) provide rapid and detailed measurement of varved sediments, and 3) identify sedimentary facies from an unsplit shallow marine sediment core. Analysis of coral cores allow us to successfully measure skeletal linear extension from annual growth bands, and provide volumetric quantification and 3D visualisation of internal bioerosion. Core-CT is an accessible, multi-use MATLAB based program that is freely available at GitHub  (https://github.com/yuting-yan/Core-CT).</p> </div><p> </p>

scholarly journals A study on the imaging characteristics of Gold nanoparticles as a contrast agent in X-ray computed tomography

2017 ◽  
Vol 23 (1) ◽  
pp. 9-14 ◽  
Author(s):  
Asghar Mesbahi ◽  
Fatemeh Famouri ◽  
Mohammad Johari Ahar ◽  
Maryam Olade Ghaffari ◽  
Seyed Mostafa Ghavami
Keyword(s):  
Computed Tomography ◽  
Contrast Media ◽  
Contrast Agent ◽  
Hounsfield Unit ◽  
Ct Number ◽  
Agent Based ◽  
X Ray ◽  
Imaging Characteristics ◽  
Tube Potential ◽  
X Ray Computed

AbstractAim: In the current study, some imaging characteristics of AuNPs were quantitatively analyzed and compared with two conventional contrast media (CM) including Iodine and Gadolinium by using of a cylindrical phantom.Methods: AuNPs were synthesized with the mean diameter of 16 nm and were equalized to the concentration of 0.5, 1, 2 and 4 mg/mL in the same volumes. A cylindrical phantom resembling the head and neck was fabricated and drilled to contain small tubes filled with Iodine, Gadolinium, and AuNPs as contrast media. The phantom was scanned in different exposure techniques and CT numbers of three studied contrast media inside test tubes were measured in terms of Hounsfield Unit (HU). The imaging parameters of the noise and contrast to noise ratios (CNR) were calculated for all studied CMs.Results: AuNPs showed 128% and 166% higher CT number in comparison with Iodine and Gadolinium respectively. Also, Iodine had a greater CT number than Gadolinium for the same exposure techniques and concentration. The maximum CT number for AuNPs and studied contrast materials was obtained at the highest mAs and the lowest tube potential. The maximum CT number were 1033±11 (HU) for AuNP, 565±10 (HU) for Iodine, 458±11 for Gadolinium. Moreover, the maximum CNRs of 433±117, 203±53, 145±37 were found for AuNPs, Iodine and Gadolinium respectively.Conclusion: The contrast agent based on AuNPs showed higher imaging quality in terms of contrast and noise relative to other iodine and gadolinium based contrast media in X-ray computed tomography. Application of the AuNPs as a contrast medium in x-ray CT is recommended.

Predicting Density and Moisture Content of Populus xiangchengensis and Phyllostachys edulis using the X-Ray Computed Tomography Technique

2020 ◽  
Vol 70 (2) ◽  
pp. 193-199
Author(s):  
Qingping Wang ◽  
Xing'e Liu ◽  
Shumin Yang
Keyword(s):  
Computed Tomography ◽  
Moisture Content ◽  
Linear Models ◽  
Physical And Mechanical Properties ◽  
Phyllostachys Edulis ◽  
Ct Number ◽  
X Ray ◽  
Ct Technique ◽  
Significant Difference ◽  
X Ray Computed

Abstract Density (D) and moisture content (MC) are two important physical properties of wood and bamboo, which are highly correlated with many other physical and mechanical properties. In this study, the X-ray computed tomography (CT) technique was used to determine the D and MC of poplar (Populus xiangchengensis) and bamboo (Phyllostachys edulis). There was a statistically significant difference in the CT-measured numbers for D and MC between these species. The D-CT and MC-CT linear models for both species were independently established: Dpoplar = 0.00098 × H + 1.02603, Dbamboo = 0.00118 × H + 0.98684, MCpoplar = 0.00309 × H + 1.89982, and MCbamboo = 0.00131 × H + 0.31488, where H is the CT number. The determination coefficients, R2, of the models were all higher than 0.97. Additionally, the R2 values obtained for model validation were also all higher than 0.97. These results indicated that it is feasible to reliably determine D and MC of wood and bamboo using the X-ray CT technique. This study aims to provide reference data for CT detection of the D and MC of wood and bamboo.

scholarly journals Assessing the representative elementary volume of rock types by X-ray computed tomography (CT) – a simple approach to demonstrate the heterogeneity of the Boda Claystone Formation in Hungary

Geologos ◽  
2021 ◽  
Vol 27 (3) ◽  
pp. 157-172
Author(s):  
Saja M. Abutaha ◽  
János Geiger ◽  
Sándor Gulyás ◽  
Ferenc Fedor
Keyword(s):  
Computed Tomography ◽  
Representative Elementary Volume ◽  
Elementary Volume ◽  
Void Space ◽  
Ct Number ◽  
X Ray ◽  
The Core ◽  
Sedimentary Structures ◽  
Rock Types ◽  
X Ray Computed

Abstract X-ray computed tomography (CT) can reveal internal, three-dimensional details of objects in a non-destructive way and provide high-resolution, quantitative data in the form of CT numbers. The sensitivity of the CT number to changes in material density means that it may be used to identify lithology changes within cores of sedimentary rocks. The present pilot study confirms the use of Representative Elementary Volume (REV) to quantify inhomogeneity of CT densities of rock constituents of the Boda Claystone Formation. Thirty-two layers, 2 m core length, of this formation were studied. Based on the dominant rock-forming constituent, two rock types could be defined, i.e., clayey siltstone (20 layers) and fine siltstone (12 layers). Eleven of these layers (clayey siltstone and fine siltstone) showed sedimentary features such as, convolute laminations, desiccation cracks, cross-laminations and cracks. The application of the Autoregressive Integrated Moving Averages, Statistical Process Control (ARIMA SPC) method to define Representative Elementary Volume (REV) of CT densities (Hounsfield unit values) affirmed the following results: i) the highest REV values corresponded to the presence of sedimentary structures or high ratios of siltstone constituents (> 60%). ii) the REV average of the clayey siltstone was (5.86 cm3) and (6.54 cm3) of the fine siltstone. iii) normalised REV percentages of the clayey siltstone and fine siltstone, on the scale of the core volume studied were 19.88% and 22.84%; respectively. iv) whenever the corresponding layer did not reveal any sedimentary structure, the normalised REV values would be below 10%. The internal void space in layers with sedimentary features might explain the marked textural heterogeneity and elevated REV values. The drying process of the core sample might also have played a significant role in increasing erroneous pore proportions by volume reducation of clay minerals, particularly within sedimentary structures, where authigenic clay and carbonate cement were presumed to be dominant.

scholarly journals Microbial Community Characteristics Largely Unaffected by X-Ray Computed Tomography of Sediment Cores

2021 ◽  
Vol 12 ◽  
Author(s):  
Erica Ewton ◽  
Scott Klasek ◽  
Erin Peck ◽  
Jason Wiest ◽  
Frederick Colwell
Keyword(s):  
Computed Tomography ◽  
Community Structure ◽  
Microbial Community ◽  
Microbial Communities ◽  
Sediment Cores ◽  
Microbial Community Composition ◽  
Ct Scanning ◽  
X Rays ◽  
X Ray ◽  
X Ray Computed

X-ray computed tomography (CT) scanning is used to study the physical characteristics of soil and sediment cores, allowing scientists to analyze stratigraphy without destroying core integrity. Microbiologists often work with geologists to understand the microbial properties in such cores; however, we do not know whether CT scanning alters microbial DNA such that DNA sequencing, a common method of community characterization, changes as a result of X-ray exposure. Our objective was to determine whether CT scanning affects the estimates of the composition of microbial communities that exist in cores. Sediment cores were extracted from a salt marsh and then submitted for CT scanning. We observed a minimal effect of CT scanning on microbial community composition in the sediment cores either when the cores were examined shortly after recovery from the field or after the cores had been stored for several weeks. In contrast, properties such as sediment layer and marsh location did affect microbial community structure. While we observed that CT scanning did not alter microbial community composition as a whole, we identified a few amplicon sequence variants (13 out of 7,037) that showed differential abundance patterns between scanned and unscanned samples among paired sample sets. Our overall conclusion is that the CT-scanning conditions typically used to obtain images for geological core characterization do not significantly alter microbial community structure. We stress that minimizing core exposure to X-rays is important if cores are to be studied for biological properties. Future investigations might consider variables, such as the length and energy of radiation exposure, the volume of the core, or the degree, to which microbial communities are stressed as important factors in assessing the impact of X-rays on microbes in geological cores.

scholarly journals Porosity prediction from X-ray computed tomography logs (RHOB and PEF) using Artificial Neural Networks (ANN)

2020 ◽  
Vol 42 (3) ◽  
pp. 141-149
Author(s):  
Andrés Felipe Ortiz ◽  
Edwar Hernando Herrera ◽  
Nicolás Santos
Keyword(s):  
Computed Tomography ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
High Resolution ◽  
Porous Space ◽  
Core Analysis ◽  
Detailed Measurement ◽  
X Ray ◽  
X Ray Computed ◽  
Artificial Neural

This work presents a method for rock porosity prediction from the X-ray computed tomography (CT) logs obtained using a double energy approach, bulk density (RHOB) and photoelectric factor (PEF). The proposed method seeks to correlate the known porosity from the Routine Core Analysis (RCAL) with RHOB and PEF high-resolution logs, as the response of these two measurements depends on the volumetric quantity of different rock materials and of the volume of its porous space. Artificial Neural Networks (ANNs) are trained so they can predict porosity from CT logs at a high resolution (0.625 mm). The ANNs validation and regression plots show that porosity predictions are good. High-resolution porosity models linked to CT images could contribute to enhancing the petrophysics model as they allow a more refined identification of intervals of interest due to the detailed measurement.

scholarly journals X-ray Computed Tomography as a Tool for Screening Sediment Cores: An Application to the Lagoons of the Po River Delta (Italy)

2021 ◽  
Vol 9 (3) ◽  
pp. 323
Author(s):  
Roberto Zonta ◽  
Giorgio Fontolan ◽  
Daniele Cassin ◽  
Janusz Dominik
Keyword(s):  
Computed Tomography ◽  
Water Content ◽  
Heterogeneous Structure ◽  
Slice Thickness ◽  
Ct Number ◽  
X Ray ◽  
X Ray Computed ◽  
Lagoon Sediments ◽  
Selection Of ◽  
Sediment Matrix

Lagoon sediments have heterogeneous structure and texture, contain shells and plants and are often highly bioturbated and disturbed by human activities. In such sediments, the selection of representative cores and the choice of a subsampling strategy are important but difficult. In this study, we examine the usefulness of X-ray computed tomography (CT) for inferring sediment features that will help in making optimal decisions prior to core opening (24 cores from seven lagoons). Various algorithms (intensity projections, slice thickness, axial and sagittal images, CT number profiles and volumetric region of interest) are tested to visualise low- and high-density volumes or objects and to quantify the relations between the average volumetric CT number and the bulk density of the sediment matrix. The CT number is related mainly to water content and indirectly to total nitrogen and <16-μm grain-size fraction (model R2 = 0.94). The outliers are attributed to a weak correspondence between the fraction of sediment sampled for water content determination and the volume of sediment matrix used for CT number measurements in highly heterogeneous sediment slices. In conclusion, CT is a powerful tool for the initial screening of cores recovered from heterogeneous lagoon sediments. The adequate use of available algorithms may provide quantitative information on various sediment features, allowing the purposeful selection of cores and subsamples for further investigation.

X-Ray Computed Tomography of Ultralightweight Metals

1999 ◽  
Vol 11 (1) ◽  
pp. 199-211
Author(s):  
J. M. Winter ◽  
R. E. Green ◽  
A. M. Waters ◽  
W. H. Green
Keyword(s):  
Computed Tomography ◽  
X Ray ◽  
X Ray Computed
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