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78 results for “SOURCE IMAGING”
Source code and data for manuscript "Large-scale deep tissue voltage imaging with targeted illumination confocal microscopy"
<p>Source code and data for manuscript "Large-scale deep tissue voltage imaging with targeted illumination confocal microscopy", <em>Nat Methods</em> (2024), https://doi.org/10.1038/s41592-024-02275-w.</p>
Source data for: Electrochemically controlled blinking of fluorophores for quantitative STORM imaging
<p>Stochastic optical reconstruction microscopy (STORM) allows widefield imaging with single-molecule resolution by calculating the coordinates of individual fluorophores from the separation of the fluorophore emission in both time and space. Such separation is achieved by photoswitching the fluorophores between a long-lived OFF state and an emissive ON state. While STORM can image single molecules, molecular counting remains challenging due to undercounting errors from photobleached or overlapping dyes and overcounting artifacts from the repetitive random blinking of the dyes. Here, we show that fluorophores can be switched electrochemically for STORM imaging (EC-STORM), with excellent control over the switching kinetics, duty cycle, and recovery yield. Using EC-STORM, we demonstrate molecular counting by using electrochemical potential to control the photophysics of dyes. The random blinking of dyes is suppressed by a negative potential but the switching ON event can be activated by a short pulsed positive potential, such that the frequency of ON events scales linearly with the number of underlying dyes. We also demonstrate the EC-STORM of tubulins in fixed cells with a spatial resolution as low as ~28 nm and counting of single Alexa 647 fluorophores on various DNA nanoruler structures. This control over fluorophore switching will enable EC-STORM to be broadly applicable in super-resolution imaging and molecular counting.</p>
Source data for "Non-Telecentric two-photon microscopy for 3D random access mesoscale 2 imaging"
<p>Source data used in a manuscript "Non-Telecentric two-photon microscopy for 3D random access mesoscale 2 imaging"</p> <p> </p> <p> </p> <p> </p>
Evolutionary Map of the Universe (EMU): discovering 18-cm OH maser sources in ASKAP continuum images of the SCORPIO field
<p>Data cubes and spectra from the ATCA C3414 project.</p> <p>Data cubes are in fits format.</p> <p>Spectra were extracted from the data cubes following what described in the text. The format is the standard output of the CASA profile tools. Each spectrum contains an header with the column description.</p>
Single cell imaging of ERK and Akt activation dynamics and heterogeneity induced by G protein-coupled receptors - Scripts & Source data
<p>Source data and scripts to reproduce the figures that are part of the publication "Single cell imaging of ERK and Akt activation dynamics and heterogeneity induced by G protein-coupled receptors".</p> <p>Journal of Cell Science (2022) 135, jcs259685, DOI: 10.1242/jcs.259685</p> <p> </p> <p>An earlier version of this work is published as a preprint: "Heterogeneity and dynamics of ERK and Akt activation by G protein-coupled receptors depend on the activated heterotrimeric G proteins", DOI: <a href="https://doi.org/10.1101/2021.07.27.453948">10.1101/2021.07.27.453948</a></p>
April 7, 2024 (v1) Image Open Tuning apicobasal polarity and junctional recycling in the hemogenic endothelium orchestrates the morphodynamic complexity of emerging pre-hematopoietic stem cells —Source data 5 relative to Figure 7 - Figure Supplement 4
<p>Source data file relative to <strong><span>Figure 7 – figure supplement 4 Panel A</span></strong></p> <p><span>Raw image of agarose gel showing the 2 alternative mRNAs encoding for ArhGEF11 in control animals (left track, control) and after injection of the MO at the one cell stage (right track, +MO at 2 and 5ng). The source data includes the raw files (native format .scn and open source format .tiff) as well as a pdf file showing both the full scale image and the cropped image selected for the figure.<br></span></p>
Combining reference-star and angular differential imaging for high-contrast imaging of extended sources - Appendix
<p>This appendix presents the disk estimations obtained with RDI, ADI, and ARDI, using IPCA, for all 60 test data sets considered in Juillard et. al. (2024). Page-sized figures shows IPCA disk estimations obtained leveraging RDI, ADI and ARDI strategies for cube 1 to 4 and disks A to E.</p> <p>Details on the data sets where disks were injected can be found in Juillard et. al. (2023) and Juillard et. al. (2024), and can be found on the Zeneodo folder : <a href="../records/11442267">https://zenodo.org/records/11442267</a></p> <p>Each page-sized figure presents the results for a specific synthetic disk in a given data set. The injected disks (A→E) are shown in the left-most column of each figure. Each figure contains three pairs of rows, each corresponding to a different injected contrast level: $10^{-3}$ (top), $10^{-4}$ (middle), and $10^{-5}$ (bottom). The top row of each pair represents the estimation, while the bottom row represents the residuals. Each column displays the following in order: ground truth (left), RDI (middle left), ADI (middle right), and ARDI (right). The best method, as determined by each metric, is indicated in the bottom-left corner of each pair of rows. The color bar bounds in the residual plots is set to $\pm$ maximum of intensity of the GT, centered at 0. For the disk image estimation plots, the color bar is adjusted for each data set to have a maximum value equal to the 99th percentile of the image. The minimal value is set to 0. Additionally, the optimal IPCA parameters (rank and number of iterations) are written at the top left of the corresponding images.</p>
Source data including NIfTI images
<p>The file src_data_conat.xlsx contains all available source data from the figures and tables. The sheets are named after the figure/table the data were used for. The sheet figs_supp_PL contains the data for Figs. S1, S13, S14, S15, S16 and Tab. S4.</p> <p> </p> <p>The zipped folder src_data_images.zip contains the (group-level) NIfTI images in MNI space shown in different figures in both the main text and supplement. Their names are prefixed with the number of the figure. Tabs. 2 and S3 were created based on the files 2B_w_CR.nii.gz and 3_CR_sig.nii.gz.</p> <p> </p> <p>The file data_validation.xlsx contains all data necessary to reproduce both the cross-sectional and longitudinal validation analyses (see subsection "CR score moderates effects of pathology on cognitive performance, also longitudinally" in the results section of the paper).</p>
Source Data Images for Figures 3a-d, Fig 4
<p>Source Data Files for Figures 3a-d, 4d</p> <p><strong>STAT5B<sup>N642H</sup> transforms T-cell subsets, resulting in differential peripheral organ infiltration.</strong></p> <p>Histological analysis using CD3, Ki67 and H&E staining of the skin, lung, liver and brain of 7- to 9-week-old wild type (WT), human STAT5B and human STAT5B<sup>N642H</sup> mice. Images are representative of three independent experiments. Original magnification: 4x (left panels in C and D), 20× and 40× (insets), scale bars = 100 μm. These images represent Source Data files for Figures 3a-d and 4d.</p> <p>Histological analysis using CD3, Ki67 and H&E staining of the liver of recipient mice transplanted with γδ T-cells from hSTAT5B<sup>N642H</sup> (n = 2) or WT (n = 1) mice. Original magnification: 20× and 40× (insets), scale bars = 100 μm.</p>
iNaturalist: iNaturalist image source file (deprecated)
<p></p>http://www.inaturalist.org/ is a place where you can record what you see in nature, meet other nature lovers, and learn about the natural world. Images and data published on EOL originate from iNaturalist Research Grade observations.<p></p><p></p>http://www.inaturalist.org/ is a place where you can record what you see in nature, meet other nature lovers, and learn about the natural world. Images and data published on EOL originate from iNaturalist Research Grade observations.
DeepPlastic: An Open Source Image Dataset for Epipelagic Marine Plastic Detection
<p>Deep Plastic</p> <ul> <li>Enhanced Object Detection for Epipelagic Plastic.</li> <li>This repository contains source code for the method developed in <a href="https://arxiv.org/pdf/2105.01882.pdf">DeepPlastic: Identifying Marine Plastic In The Epipelagic Zone using Computer Vision and Deep Learning</a></li> <li> <p>Information:</p> </li> <li>Paper: [Coming Soon]</li> <li>YouTube video of Results: <a href="https://youtu.be/8zBdFxaK4Os">https://youtu.be/8zBdFxaK4Os</a></li> <li> <p>Object Detection Model</p> </li> <li>Four models: YOLOv4, YOLOv5, MobileSSD, Faster RCNN Inception V2</li> <li>Small efficient and high precision models can be used for real-time object detection.</li> <li>Model architecture and implementation details: <a href="https://arxiv.org/">https://arxiv.org/</a></li> <li>Weights for YOLOv4 and YOLOv5 are provided in the model/ <ul> <li>YOLOv4: best. weights; use <a href="https://drive.google.com/file/d/1YOTtZ2cHbqgxHukzLp01OVsUoa2CwwXs/view?usp=sharing">best.weights</a></li> <li>YOLOv5: best.pt; use <a href="https://drive.google.com/file/d/14mBOhtLrE2d3hudqjwBZmawKAvTF4zxS/view?usp=sharing">best.pt</a></li> </ul> </li> <li> <p>Google Colab Links</p> <p>Note: Click on File and Save Copy in Drive. If you try to edit my file it'll ask you for permission and send me an email. Please make your own copy.</p> </li> <li>YOLOv5: <a href="https://colab.research.google.com/drive/1_qzbpBWkNfxQ0ny-DvsKicCeM0aFU4eW?usp=sharing">https://colab.research.google.com/drive/1_qzbpBWkNfxQ0ny-DvsKicCeM0aFU4eW?usp=sharing</a></li> <li> <p>DeepTrash DataSet</p> </li> <li>1900 training images, 637 test images, 637 validation images (60, 20, 20 split)</li> <li>Field images taken from Lake Tahoe, San Francisco Bay and Bodega Bay in CA.</li> <li>Deep Sea images are from JAMSTEK JEDI dataset: <a href="http://www.godac.jamstec.go.jp/">http://www.godac.jamstec.go.jp/</a></li> </ul>
OCTAVA: an open-source toolbox for quantitative analysis of optical coherence tomography angiography images
<p>This is a dataset of OCTA images used in the development of the manuscript <em>OCTAVA: an open-source toolbox for quantitative analysis of optical coherence tomography angiography images</em></p>
Literature review of Design in Open Source Agriculture - Images
<p>Literature review of Design in Open Source Agriculture - Images</p> <ol> <li>Fig. 1. Publications by subject areas</li> <li>Fig. 2. Publications by country</li> <li>Fig. 3. Yearly output of publications</li> <li>Fig. 4. Network of co-authorship (generated with VOSviewer) <em>(Extra image not included in the article)</em></li> <li>Fig. 5. Network of co-citation (generated with VOSviewer) <em>(Extra image not included in the article)</em></li> <li>Fig. 6. Network of bibliographic coupling(generated with VOSviewer) <em>(Extra image not included in the article)</em></li> <li>Fig. 7. Co-word analysis: network of terms from title and abstract (generated with VOSviewer) <em>(Extra image not included in the article)</em></li> <li>Fig. 8. Co-word analysis: network of keywords (generated with VOSviewer) <em>(Extra image not included in the article)</em></li> <li>Fig. 9. Thematic Map based on Authors’ keywords (generated with bibliometrix) <em>(Extra image not included in the article)</em></li> <li>Fig. 10. Thematic Map based on Titles (just single words - unigrams) (generated with bibliometrix) <em>(Extra image not included in the article)</em></li> <li>Fig. 11. Thematic Map based on Abstracts (just single words - unigrams) (generated with bibliometrix) <em>(Extra image not included in the article)</em></li> <li>Fig. 12. Trend Topics (generated with bibliometrix) <em>(Extra image not included in the article)</em></li> </ol>
Anxa1-iCre and Aldh1a1-iCre Raw Image Source Data for Azcorra, Gaertner et al
<p>Raw, unprocessed microscopy image data in multichannel tif format for IF images from Anxa1-iCre and Aldh1a1-iCre validation, localization, and projection mapping experiments. Image files are names according to the figure and panel which they apply to.</p>
Source data for VALIS: Virtual Alignment of pathoLogy Image Series for multi-gigapixel whole slide images publication
<p>Source data used to create figures in <em>VALIS: Virtual Alignment of pathoLogy Image Series for multi-gigapixel whole slide images</em> (Nature Communications, 2023)</p>
Myocardial Stress Perfusion Imaging With Dual Source CT
ClinicalTrials.gov study NCT00853671. IPD Sharing: Not stated. Countries: 1. Publications: 8.
Source data for: Electrochemically controlled blinking of fluorophores for quantitative STORM imaging
Open the record for dataset details and reuse information.
Mapping built infrastructure in semi-arid systems using data integration and open-source approaches for image classification
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Supplementary Dataset for Detecting structured sources in noisy images via Minkowski maps
<p>Supplementary Dataset of the publication "<a href="https://dx.doi.org/10.1209/0295-5075/128/60001">Detecting structured sources in noisy images via Minkowski maps</a>" by the same authors:</p> <p>M. A. Klatt, K. Mecke. <em>EPL (Europhysics Letters)</em> <strong>128</strong>:60001 (2019)<br> <a href="https://dx.doi.org/10.1209/0295-5075/128/60001">https://dx.doi.org/10.1209/0295-5075/128/60001</a></p> <p>The dataset contains all simulated data and parameters of the figures and table in the main text and supplementary material.</p> <p>The corresponding code is available at the GitHub repository:<br> <a href="https://github.com/michael-klatt/minkmaps">https://github.com/michael-klatt/minkmaps</a></p>
Image distortion data from "An open-source MRI compatible frame for multimodal presurgical mapping in macaque and capuchin monkeys"
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ScienceDex guides
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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.