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187 results for “digital imaging”
Digital image correlation experiments involving in-plane loading of a composite laminate
<div>----------------------------------------------------------------------------------------------------------------------------------------------------------------------</div> <div>-------------------------------------------------------------------------------- <strong>SUMMARY</strong> ---------------------------------------------------------------------------</div> <div>----------------------------------------------------------------------------------------------------------------------------------------------------------------------</div> <div> </div> <div>Stereo-DIC 5 MPx system was used to perform experiments on a composite laminate.</div> <div>Thickness = 2.48 mm</div> <div>Layup is [0, 45 -45 90]2s leading to quasi-isotropic behaviour</div> <div> </div> <div>----------------------------------------------------------------------------------------------------------------------------------------------------------------------</div> <div>-------------------------------------------------------------------------------- <strong>FOLDERS </strong>---------------------------------------------------------------------------</div> <div>----------------------------------------------------------------------------------------------------------------------------------------------------------------------</div> <div> </div> <div><strong>Image sets: </strong> </div> <div><strong>Sample 1:</strong> monotonically loaded up to 7.2 kN. <br><strong>Sample 2: </strong>monotonically loaded up to 10 kN.<br><strong>Sample 3:</strong> loaded cyclically with increasing peak load to study the presence of permanent strains.</div> <div> </div> <div><strong>Each folder contains the following subfolders:</strong></div> <div><strong>stationary: </strong>stationary images for DIC noise evaluation</div> <div><strong>calib: </strong>calibration target images for stereo-DIC calibration using MatchID software</div> <div><strong>test: </strong>images of the test sample being loaded, with force.csv including load reading from the uniaxial test bench synced with the images. </div> <div> </div> <div> </div> <div>----------------------------------------------------------------------------------------------------------------------------------------------------------------------</div> <div>------------------------------------------------------------------------ <strong>SUPPORTING NINFORMATION </strong>--------------------------------------------------------------------</div> <div>---------------------------------------------------------------------------------------------------------------------------------------------------------------------- </div> <div> </div> <div>Each calibration image folder contains a *.caldat file with intrinsic and extrinsic stereo camera parameters identified by MatchID 2024.2 DIC package.</div>
Digital breast tomosynthesis and contrast-enhanced dual-energy digital mammography alone and in combination compared to 2D digital synthetized mammography and MR imaging in breast cancer detection and classification
<p>We uploaded the dataset of included patients of manuscript: Petrillo A, Fusco R, Vallone P, Filice S, Granata V, Petrosino T, Rosaria Rubulotta M, Setola SV, Mattace Raso M, Maio F, Raiano C, Siani C, Di Bonito M, Botti G. Digital breast tomosynthesis and contrast-enhanced dual-energy digital mammography alone and in combination compared to 2D digital synthetized mammography and MR imaging in breast cancer detection and classification. Breast J. 2020 May;26(5):860-872. doi: 10.1111/tbj.13739. Epub 2019 Dec 30. PMID: 31886607.</p>
digital forensic AND imaging
<p>upload dari lens.org</p>
Dataset for image-based geometric digital twinning for stone masonry elements
<p>This is the dataset used to assess the performance of the geometrical digital twinning algorithm proposed by Pantoja-Rosero et, al (2023) in the article "Image-based geometric digital twinning for stone masonry elements" (<a href="https://doi.org/10.1016/j.autcon.2022.104632">https://doi.org/10.1016/j.autcon.2022.104632</a>)</p>
Dataset for image-based geometric digital twinning for stone masonry elements - part 2
<p>This is the dataset used to assess the performance of the geometrical digital twinning algorithm proposed by Pantoja-Rosero et, al (2023) in the article "Image-based geometric digital twinning for stone masonry elements" (<a href="https://doi.org/10.1016/j.autcon.2022.104632">https://doi.org/10.1016/j.autcon.2022.104632</a>)</p>
Processing steps to generate a Digital Surface Model based on SPOT-7 tri-stereo images published in the study "An assessment of the effects of DEM quality and spatial resolution on a model for mapping lahar inundation areas at volcan Copahue (Argentina & Chile)" in the Journal of South American Earth Sciences https://doi.org/10.1016/j.jsames.2022.104138
<p>The Digital Surface Model (DSM) was created from SPOT-7 tri-stereo images for the Copahue volcano between the border of Argentina and Chile. Two versions of the DSM are provided: an unfiltered product and a final, filtered product. The final product has a spatial resolution of 5-m and was used for lahar inundation modeling for the Copahue volcano (Viotto, Toyos, and Bookhagen 2022, <a href="https://doi.org/10.1016/j.jsames.2022.104138">https://doi.org/10.1016/j.jsames.2022.104138</a> : An assessment of the effects of DEM quality and spatial resolution on a model for mapping lahar hazard inundation at Volcán Copahue (Argentina & Chile). <em>Journal of South American Earth Sciences</em> ). The dataset provided should be cited together with the article. </p> <p><strong>DSM processing </strong></p> <p>The source images were given by a SPOT-7 snow- and cloud-free triplet (Nadir, Backward and Forward) of 1.5 m spatial resolution from 19 April 2018 (SPOT Image, Airbus Defence and Space GmbH, distributed by CONAE; Dataset ID: <em>SEN_SPOT7_20180419_142955500_000</em>, delivered by CONAE as <em>DS_SPOT7_20180419</em>).</p> <p>The data were processed with the suite of digital photogrammetry tools AMES Stereo Pipeline ASP (Beyer et al., 2018). The procedure for the generation of the DSM is summarized by following steps: </p> <ol> <li> <p>The orbital parameters (RCP models) were adjusted using the bundle adjustment tool with no ground control points, since they were unavailable.</p> </li> <li> <p>The scenes were map-projected onto the NASADEM (spatial resolution of 30 m) elevation dataset, assisted by the results of the orbital adjustment in Step 1.</p> </li> <li>The stereo correlation of the map-projected scenes including the results of the adjusted orbital parameters, was performed three times, using as first scene (i.e., primary image) the nadir (N), backward (B), and forward (F) images . In each run, the order of images to perform the stereo correlation was: N-F-B, F-N-B, and B-N-F. Thus, three point clouds were generated. Specific ASP correlator settings (other than defaults parameters; for details see the provided stereo-default file) were set in the following way: <em>Correlation Kernel</em>: 15 x 15 pixels; <em>Sub-pixel Refinement Kernel</em>: 21 x 21 pixels; <em>Subpixel Refinement Mode</em>: 2 (Weighted Affine Adaptive Window Correlator EM)</li> <li> <p>The three point clouds were merged into one point cloud with a regular grid of 5 m (unfiltered product, known as <em>DSM_Copahue_UTM19S_WGS84_5m_raw.tif</em>).</p> </li> </ol> <p>The quality of the final point cloud was assessed by comparing the unfiltered DSM with a spatial resolution of 12-m against the WorldDEM<sup>TM</sup> elevation dataset (Collins et al., 2015). The WorldDEM was provided by Airbus Defence and Space GmbH under license for the scope of the Viotto et al., 2022 study. The comparison of the pixel-to-pixel heights above the ellipsoid (WGS84) between the two datasets resulted in a mean difference of 0.67 m and a standard deviation of +/- 4.82 m. </p> <p>Comprehensive details on the methodologies evaluated to create the dataset with ASP, can be found in the corresponding master's thesis “Topografía digital y modelado de lahares en el Volcán Copahue, Argentina-Chile” from S. Viotto (link: https://rdu.unc.edu.ar/handle/11086/15384). Recommended literature about processing DEMs from SPOT imagery is given by Mueting et al., 2021 (<a href="https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021JF006330">https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021JF006330</a>). </p> <p><strong>Creation of the Final, Filtered DSM product</strong></p> <p>The corrections and improvements applied to the unfiltered product to create the final, filtered DSM (named DSM_Copahue_UTM19S_WGS84_5m_VoidFilled.tif) are summarized by following steps. </p> <p> </p> <ol> <li> <p><em>Water Bodies Delineation</em></p> </li> </ol> <p>The delineation of the water bodies was based on a mask created from the free access water bodies datasets provided by the Instituto Geográfico Nacional of Argentina (<a href="https://www.ign.gob.ar/NuestrasActividades/InformacionGeoespacial/CapasSIG">https://www.ign.gob.ar/ NuestrasActividades/InformacionGeoespacia l/CapasSIG</a>) and by the Ministerio de Bienes Nacionales in Chile ( <a href="https://www.ide.cl/index.php/aguas-continentales/item/1508-catastro-de-lagos">https://www.ide.cl/index.php /aguas-continentales/item/1508-catastro-de-lagos</a>). A total of 45 lakes within the area of interest were considered. Lakes with areas below or equal to 25 m2 were smoothed with a median filter in the last step. Lakes with areas above this threshold were filled in with a constant value and their borders were smoothed with a median filter to provide smooth shorelines.</p> <p><em>2 . Void Filling</em></p> <p>Voids (other than water bodies) were filled with the tool “Close Gaps” from Saga GIS software. </p> <p><em>3. Smoothing</em></p> <p>Finally, the elevation dataset was smoothed with a median filter using a 3 x 3 pixel window, excluding water bodies filled in the step 1. </p> <p><strong>Final Remarks and Suggestion</strong></p> <p>The quality assessment of the final version by visual inspection of the hillshades suggested an improvement of the signal to noise ratio. However, the void filling process may be improved.</p> <p><br> </p> <p><strong>Dataset Description</strong></p> <table align="center"> <caption> </caption> <tbody> <tr> <td>Digital Surface Models</td> <td> <p>No Data Value = -9999</p> <p>Format = float 32 bit</p> <p>File Format = GeoTiff</p> <p>Vertical Datum: WGS84</p> <p>Projection information: EPSG 32719 (UTM19S)</p> <p>Spatial Resolution: 5m (subfix: <em>_5m</em>) </p> <p>Versions: </p> <ul> <li> <p>Unfiltered product: without corrections <em>DSM_Copahue_UTM19S_WGS84_5m_raw.tif</em></p> </li> <li> <p>Final, filtered product: smoothed and void filled <em>DSM_Copahue_UTM19S_WGS84_5m_VoidFilled.tif</em></p> </li> </ul> </td> </tr> <tr> <td>Water Bodies Mask</td> <td> <p>No Lake Value = 0</p> <p>Lakes Values = 1 to 45</p> <p>File Format= GeoTiff</p> <p>Spatial Resolution: 5m (subfix: <em>_5m</em>)</p> <p>Projection information : EPSG 32719 (UTM19S)</p> <p><em>WB_mask_5m_UTM19S.tif</em></p> </td> </tr> </tbody> </table> <p> </p> <p> </p> <p><strong>Repository structure</strong></p> <p>|__ 01_Scripts</p> <p> |+ run21_CopahueDSM_AMES_sviotto.sh</p> <p> |+ stereo.default</p> <p>|__ 02_DSMs</p> <p> |+ DSM_Copahue_UTM19S_WGS84_5m_raw.tif</p> <p> |+ DSM_Copahue_UTM19S_WGS84_5m_VoidFilled.tif</p> <p> |+ WB_mask_5m_UTM19S.tif</p> <p><strong>References</strong></p> <p>Beyer, R. A., Alexandrov, O., & McMichael, S. (2018). The Ames Stereo Pipeline: NASA's open source software for deriving and processing terrain data. <em>Earth and Space Science</em>, 5, 537– 548. <a href="https://doi.org/10.1029/2018EA000409">https://doi.org/10.1029/2018EA000409</a></p> <p>Collins, J., Riegler, G., Schrader, H., Tinz, M., 2015. Applying terrain and hydrological editing to TanDEM-X data to create a consumer-ready worlddem product. Int. Arch. Photogram. Rem. Sens. Spatial Inf. Sci. 40 (7), 1149. https://doi.org/10.5194/isprsarchives-XL-7-W3-1149-2015.</p> <p>Mueting, A., Bookhagen, B., & Strecker, M. R. (2021). Identification of debris-flow channels using high-resolution topographic data: A case study in the Quebrada del Toro, NW Argentina. <em>Journal of Geophysical Research: Earth Surface</em>, 126, e2021JF006330. <a href="https://doi.org/10.1029/2021JF006330">https://doi.org/10.1029/2021JF006330</a></p> <p>Viotto, S., Toyos, G., & Bookhagen, B. (2022). An assessment of the effects of DEM quality and spatial resolution on a model for mapping lahar hazard inundation at volcán copahue (Argentina & Chile). Journal of South American Earth Sciences, 104138. https://doi.org/10.1016/j.jsames.2022.104138</p> <p> </p> <p> </p>
Physics-driven universal twin-image removal network for digital in-line holographic microscopy - dataset
<p>Dataset (Matlab files) containing holograms and reference reconstructions employed in:<br> <br> M. Rogalski, P. Arcab, L. Stanaszek, V. Micó, C. Zuo and M. Trusiak, "Physics-driven universal twin-image removal network for digital in-line holographic microscopy", Submitted 2023<br> <br> This dataset should be used together with the codes present at:<br> https://github.com/MRogalski96/UTIRnet</p>
Digitally edited images.
<p>Digitally edited images of male and female models.</p>
Digital Image Correlation in Right Ventricular Evaluation
ClinicalTrials.gov study NCT03115294. IPD Sharing: NO. Countries: 1. Publications: 2.
Clinical Validation of a 'Hand-held' Fluorescence Digital Imaging Device for Wound Care Applications
ClinicalTrials.gov study NCT01378728. IPD Sharing: Not stated. Countries: 1. Publications: 1.
An Evaluation of a Self-contained Direct Digital Radiography System for Breast Specimen Imaging
ClinicalTrials.gov study NCT01379092. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Evaluation of a 'Hand-held' Fluorescence Digital Imaging Device for Real-Time Advanced Wound Care Monitoring (JDRTC/UHN)
ClinicalTrials.gov study NCT01651845. IPD Sharing: NO. Countries: 1. Publications: 1.
Digital Quantification of Dental Plaque Based on Intraoral Scanner Images
ClinicalTrials.gov study NCT07152314. IPD Sharing: NO. Countries: 1. Publications: 1.
Differentiating three Indian shads by applying shape analysis from digital images
Open the record for dataset details and reuse information.
Hematoxylin-and-eosin-stained bladder urothelial cell carcinoma versus inflammation digital histopathology image dataset
Open the record for dataset details and reuse information.
Data from: Automated leaf physiognomic character identification from digital images
Open the record for dataset details and reuse information.
Using Delaunay triangulation to sample whole-specimen color from digital images
Open the record for dataset details and reuse information.
Maximizing human effort for analyzing scientific images: a case study using digitized herbarium sheets
<p>This directory contains "gold standard" set of phenological annotations of herbarium specimen photographs, in Acer_Prunus_gold_standard_phenological_data.csv. The methods used to generate these data are described in Brenskelle, L., R. P. Guralnick, M. Denslow, and B. J. Stucky. 2020. Maximizing human effort for analyzing scientific images: A case study using digitized herbarium sheets. Applications in Plant Sciences 8(6): e11370.</p>
Digital image correlation (DIC) measurement of contact stiffness
<p>Measurements with digital image correlation of normal and tangential contact stiffness for ground Ti-6Al-4V interfaces suggest a linear relationship between normal contact stiffness and normal load and a linear relationship between tangential contact stiffness and tangential load. The normal contact stiffness for these surfaces is observed approximately to be inversely proportional to an equivalent surface roughness parameter, defined for two surfaces in contact. The ratio of the tangential contact stiffness to the normal contact stiffness at beginning of a load step is seen to be given approximately by the Mindlin ratio. A simple empirical model is proposed to estimate both normal and tangential contact stiffness at different loads for ground Ti-6Al-4V surfaces of known surface roughness and coefficient of friction.</p>
Supplementary material 1 from: Thanayutsiri T, Charoenying T, Patrojanasophon P, Pamornpathomkul B, Opanasopit P, Ngawhirunpat T, Rojanarata T (2023) Facile, sensitive and reagent-saving smartphone-based digital image colorimetric assay of captopril tablets enabled by long-pathlength RGB acquisition. Pharmacia 70(4): 1511-1519. https://doi.org/10.3897/pharmacia.70.e114927
Supplementary data
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.