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979
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ShareScore release 0.9.0
Dataset results
979 results for “image dataset”
DsCGF: A large-scale open image dataset for deep learning enabled intelligent sorting and analyzing of raw coal (part 1)
Open the record for dataset details and reuse information.
DsCGF: A large-scale open image dataset for deep learning enabled intelligent sorting and analyzing of raw coal (part 3)
Open the record for dataset details and reuse information.
Test Dataset for 3D semantic image segmentation of the Liver and Tumor
Open the record for dataset details and reuse information.
A Multi-Scale Neuron Morphometry Dataset from Peta-voxel Mouse Whole-Brain Images
<p><span>Neuron morphology and sub-neuronal patterns offer vital insights into cell typing and the structural organization of brain networks. The community-collaborative BRAIN Initiative Cell Census Network (BICCN) project has yielded a vast amount of whole-brain imaging data. However, reconstructing multi-scale neuron morphometry at a whole-brain scale requires not only the integration of diverse hardware devices, tools, and algorithms but also a dedicated production workflow. To address these challenges, we developed a cloud-based, collaborative platform capable of handling peta-scale imaging data. Using this platform, we generated the largest multi-scale morphometry dataset from hundreds of sparsely labeled mouse brains. The morphometry dataset comprises 182,497 annotated cell bodies, 15,441 locally traced morphologies, and 1,876 fully reconstructed morphologies. We also identified sub-neuronal arborizations for both axons and dendrites, along with the primary axonal tracts connecting them. In addition, we identified 2.63 million putative boutons. All morphometric data were registered to the Allen Common Coordinate Framework (CCF) atlas. The morphometry dataset has proven to be an invaluable resource for whole-brain cross-scale morphological studies in mouse.</span></p>
Dataset of images SfM - FRM - Lighting and Artificial texture - JPG
<p>This collection of images was employed to examine the impact of various configurations in the 3D modeling process for short-distance environments. This analysis established settings to achieve submillimeter accuracy in the RMSE values of the analyzed points. </p> <p>Set of images used to evaluate the use of light aids (softboxes) and artificial textures in a short-distance environment. This set was used to evaluate the configurations and the possibility of using the SfM technique in the 3D modeling of structural tests. Test specimens used (Concrete, Metal and Wood)—artificial texture in white Chalk (on Concrete and Wood) and red marker (on metal).<br>Texture patterns were drawn in a checkerboard fashion (T1) and a more closed checkerboard shape (T2).</p> <p>Images in JPG without compression.</p>
Dataset for Phase-Diverse Imaging and Models for Real-World Aberration Correction
<p>The work is currently submitted for publication.</p>
Soybeans-Tempeh-Image-Dataset-for-Tempeh-Maturity-Detection
Repository for Soybeans Tempeh Image Dataset for Tempeh Maturity Detection
Data from: An extensive dataset of eye movements during viewing of complex images
We present a dataset of free-viewing eye-movement recordings that contains more than 2.7 million fixation locations from 949 observers on more than 1000 images from different categories. This dataset aggregates and harmonizes data from 23 different studies conducted at the Institute of Cognitive Science at Osnabrück University and the University Medical Center in Hamburg-Eppendorf. Trained personnel recorded all studies under standard conditions with homogeneous equipment and parameter settings. All studies allowed for free eye-movements, and differed in the age range of participants (~7-80 years), stimulus sizes, stimulus modifications (phase scrambled, spatial filtering, mirrored), and stimuli categories (natural and urban scenes, web sites, fractal, pink-noise, and ambiguous artistic figures). The size and variability of viewing behavior within this dataset presents a strong opportunity for evaluating and comparing computational models of overt attention, and furthermore, for thoroughly quantifying strategies of viewing behavior. This also makes the dataset a good starting point for investigating whether viewing strategies change in patient groups.
Image dataset from Automatic analysis of Trypanosoma cruzi: A machine learning approach for the detection of blood trypomastigotes in low resolution images
<p>Image files of mice blood smear containing <em>T. cruzi</em> trypomastigotes. The images were used to train and test the classification model of the objects (nuclei and/or kinetoplasts) present in the images.</p>
Imaging dataset for positron emission microscopy of patient-derived tumor organoids
<p>Here, we present a microscopy method to image <sup>18</sup>F-fluorodeoxyglucose and other radiotracers in patient-derived tumor organoids with spatial resolution up to 100-fold better than that of clinical positron emission tomography (PET). When combined with brightfield imaging, this metabolic imaging approach functionally mirrors clinical PET/CT scans and provides a quantitative readout of cell glycolysis other metabolic processes. </p>
Dataset and CNN code for DECam CNN Difference Imaging Artifact Paper
<p>Dataset and code to accompany the paper listed at: https://arxiv.org/abs/2106.11315v1</p>
DATASETS - Integration of Non-Destructive Acoustic Imaging investigation with Photogrammetric and Morphological Analysis to Study the "Graecia Vetus" in the Chigi Palace of Ariccia
<p>Datasets of an integrated investigation on the monochrome painting "Graecia Vetus" located in the Ariosto Room in the historical Chigi Palace of Ariccia.</p> <p>Three datasets including:</p> <p>- <strong>Dense Cloud from the surface morphological investigation of the surface by Photogrammetric Survey:</strong></p> <p>1. Zip file containing the "*.obj", "*.mtl", "*.jpg" files to open the Model.</p> <p><strong>- Four matrices from structural damage investigation of the painting by Frequency Resolved Acoustic Imaging:</strong></p> <p>1. Integrated Acoustic Image (IAI) in the wideband (500 - 12,000) Hz;</p> <p>2. Frequency Resolved Acoustic Image (FRAI) in the narrow frequency band 1/3 octave band centred at 1000 Hz;</p> <p>3. Frequency Resolved Acoustic Image (FRAI) in the narrow frequency band 1/3 octave band centred at 6300 Hz;</p> <p>4. Frequency Resolved Acoustic Image (FRAI) in the narrow frequency band 1/3 octave band centred at 10,000 Hz.</p> <p><strong>- One profile and one matrix from structural damage investigation of the wall by Sonic Tests with Impact Hammer:</strong></p> <p>1. Relative variation of pulse velocity along the horizontal axis;</p> <p>2. Tomographic map of the relative variation of pulse velocity inside the wall</p>
Dataset for the paper "A boundary-guided transformer based method for measuring distance from rectal tumor to anal verge on magnetic resonance images"
<p>A sagittal MR rectal image dataset for the field of DTAV measurement.</p>
Road Condition Image Dataset
<p>Datasets containing 2D images from roads. The images were either rendered from 3D lidar point clouds or captured by a camera on a so called Mobile Mapping vehicle. For more information on how to use this dataset, visit the following repository:</p> <p>https://github.com/Snagnar/CompetitiveReconstructionNetworks</p>
Dataset of Road images, divided in images with and without damages
<p>This dataset contains images from roads, which are labeled as healthy and damaged. The images are either rendered from 3D lidar point clouds or captured by a camera mounted on a mobile mapping vehicle.</p> <p>For more information on how to use this dataset, refer to the following github repository: https://github.com/Snagnar/CompetitiveReconstructionNetworks</p> <p> </p>
A Dataset of Annotated Histopathological Images for Tumor Cellularity Assessment in Breast Cancer
<p>The dataset consists of 2 H&E whole slide images, captured at a magnification of 40×, which overall contains tens of thousands of tumor nuclei from patients with breast cancer. The annotations, which consist of tumor and non-tumor nuclei, were provided by an expert pathologist, using the QuPath software. In detail, within the indicated ROIs, 1419 tumor-nuclei and 605 non-tumor-nuclei were labeled for a total of 2024 nuclei (respectively 762 and 381 from the first WSI, 657 and 224 from the second WSI).</p> <p>The institutional Ethic Committee of the IRCCS Istituto Tumori Giovanni Paolo II approved the study -- Prot n. 8/CE (February 2, 2021).</p>
Image Dataset
<p>Image dataset</p>
afids-data: Magnetic resonance imaging datasets with anatomical fiducials for quality control and registration
<p>Curated anatomical landmarks placements for common neuroimaging templates and datasets.</p>
Dataset for "Imaging frontside and backside attack in radical ion-molecule reactive scattering"
<p>Dataset for "Imaging frontside and backside attack in radical ion-molecule reactive scattering"</p>
Dataset with results of "Joint 2D to 3D image registration workflow for comparing multiple slice photographs and CT scans of apple fruit with internal disorders"
<p><strong>Summary</strong></p> <p>This dataset contains all results from the paper "Joint 2D to 3D image registration workflow for comparing multiple slice photographs and CT scans of apple fruit with internal disorders". Most notably, this dataset contains the corresponding CT slices for slice photographs of 1347 'Kanzi' apples. This dataset also contains data of the results section, metadata required to make the registration code run, and segmentation masks of the apple slice photographs. The "raw" data that was used to produce these results can be found in another Zenodo dataset: <a href="../record/8167285">https://zenodo.org/record/8167285</a>.</p> <p><br><strong>Description</strong></p> <ul> <li><strong>registered ct photo side-by-side view.zip </strong>is the easiest way to explore the registered CT photo image pairs. For every apple slice it contains a .png image consisting of the slice photo, registered CT slice and a combined view (photo=green, CT=purple) side-by-side. The resolution was reduced to reduce the file size.</li> <li><strong>registered ct slices.zip </strong>contains the full resolution CT slices as .tiff files. The matching slice photos can be found in <strong>slice_photos_crop.zip</strong> in <a href="../record/8167285">https://zenodo.org/record/8167285</a>.</li> <li><strong>photo metadata.zip </strong>contains all metadata files required to run the code on <a href="https://github.com/D1rk123/apple_photo_ct_workflow">https://github.com/D1rk123/apple_photo_ct_workflow</a>.</li> <li><strong>results.zip</strong> contains the IPCED annotations and per apple metrics that were used to calculate all the average metrics and tables in the results section of the paper.</li> <li><strong>subset experiment registered annotation slice.zip </strong>contains the full resolution CT slices of the annotation slice in the subset experiment as .tiff files.</li> <li><strong>segmentation masks.zip </strong>contains slice photo segmentation masks as .png images. There are subfolders for the training set, the test set and the masks used for the workflow in the paper.</li> </ul> <p><br><strong>Research group</strong><br>This dataset was produced by the Computational Imaging group at Centrum Wiskunde & Informatica (CI-CWI) in Amsterdam, The Netherlands: <a href="https://www.cwi.nl/research/groups/computational-imaging">https://www.cwi.nl/research/groups/computational-imaging</a></p> <p><strong>Contact details</strong><br>dirk [dot] schut [at] cwi [dot] nl</p> <p><strong>Acknowledgments</strong><br>This work was funded by the Dutch Research Council (NWO) through the UTOPIA project (ENWSS.2018.003).</p>
ScienceDex guides
Understand access before you commit
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.