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datasets available to search
ShareScore release 0.9.0
Dataset results
469 results for “Image analysis”
Soil images in DICOM format including Python programs for data transformation, 3D analysis, CNN traininig, CNN analysis
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Data from: Towards a framework for agent-based image analysis of remote-sensing data
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Data from: Comparing analysis methods in functional calcium imaging of the insect brain
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Data from: Quantification and statistical analysis methods for vessel wall components from stained images with Masson's trichrome
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Data from: Dissecting the phenotypic components of crop plant growth and drought responses based on high-throughput image analysis
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Data from: Image Calibration and Analysis Toolbox – a free software suite for measuring reflectance, colour, and pattern objectively and to animal vision
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STAMP: Single-Cell Transcriptomics Analysis and Multimodal Profiling through Imaging [CosMx Spatial]
GEO Series GSE290466. Homo sapiens. 92 samples. Type: Other.
STAMP: Single-Cell Transcriptomics Analysis and Multimodal Profiling through Imaging [Xenium]
GEO Series GSE301112. Mus musculus; Homo sapiens. 63 samples. Type: Other.
3D imaging and single-cells analysis reveal cellular heterogeneity of lymphatic valve endothelial cell types
GEO Series GSE295984. Mus musculus. 1 samples. Type: Expression profiling by high throughput sequencing.
Identification of Prognostic Biomarkers of Ovarian High Grade Serous Carcinoma through Spatial Transcriptome Analysis and Multispectral imaging
GEO Series GSE279969. Homo sapiens. 69 samples. Type: Other.
STAMP: Single-Cell Transcriptomics Analysis and Multimodal Profiling through Imaging [Merscope]
GEO Series GSE301544. Homo sapiens; synthetic construct. 12 samples. Type: Other.
Reliability of 3D image analysis and influence of contrast medium administration on measurement of Hounsfield unit values of the proximal femur
<p>These datasets consists of three PDF files for intraobserver ICC, interobserver ICC and effect of contrast medium administration.</p>
Data and supplementary material for the paper "A simple image analysis technique for measuring bed surface texture in flume experiments"
<p>This repository contains the Matlab codes developed for the image processing illustrated in the paper "A simple image analysis technique for measuring bed surface texture in flume experiments" submitted to the Journal of Hydrology. Results of the image processing are reported in some excel spreadsheets. We also provide the pdf file of the paper "Morphology, bedload and sorting process variability in response to lateral confinement: results from physical models of gravel-bed rivers" illustrating the laboratory experiments for which we developed the image analysis technique presented in "A simple image analysis technique for measuring bed surface texture in flume experiments". The paper titled "Morphology, bedload and sorting process variability in response to lateral confinement: results from physical models of gravel-bed rivers" has not been published yet, but it has been accepted by the Journal of Geophysical Research - Earth Surface. Thus, we provide the editor acceptance letter as well.</p>
Symbrain: A large-scale dataset of MRI images for neonatal brain symmetry analysis
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Comparative Analysis of Intraoperative Imaging Technologies in Neurosurgical Applications
<p><br>The image provides a comparative overview of four different intraoperative imaging technologies utilized in neurosurgery and other medical fields: Intraoperative CT (Computed Tomography), Intraoperative MRI (Magnetic Resonance Imaging), Intraoperative USG (Ultrasonography), and O-Arm Imaging System.I have created it based on my 15 years of experience working first hand with them, individually. </p><p><strong>Intraoperative CT</strong> offers high-resolution imaging and excellent bone detail, making it suitable for a broad range of applications including neurosurgery, orthopedics, and trauma. It is relatively fast but involves radiation exposure, which is a consideration in pediatrics and repeated procedures. The installation cost ranges from approximately $1 to $2.5 million, with moderate running costs.</p><p><strong>Intraoperative MRI</strong> is noted for its superior soft tissue contrast and is most ideal for brain, spinal cord, and nerve imaging. It is primarily used in neurosurgery and has higher installation and running costs, approximately $2 to $4 million, partly due to the need for maintenance and staff. Its benefits include excellent soft tissue detail and the absence of radiation exposure, but it has longer scan times and is sensitive to movement.</p><p><strong>Intraoperative USG</strong> is good for real-time imaging and is mostly used for abdominal, cardiac, and biopsy procedures. It is safe, with no radiation exposure, and comfortable for patients. Its cost-effectiveness is highlighted, with equipment costs ranging from $20,000 to $100,000, and it has low running costs. However, it has limited bone imaging capabilities and depth resolution.</p><p><strong>O-Arm Imaging System</strong> provides high-quality 2D and 3D images, making it suitable for spinal and orthopedic surgery. Its installation cost is similar to that of intraoperative CT, between $1 to $2.5 million, with moderate running costs. It offers fast imaging and is adaptable to surgical workflow but requires a specific OR setup compatible with navigation systems.</p><p>Each technology has its specific benefits and limitations, with the choice of the appropriate imaging system depending on the surgical situation, patient safety considerations, and cost factors.</p>
Fluorescence image time series for pair correlation function analysis
<p>Data files for the tutorial "<a href="https://github.com/cgohlke/ipcf.ipynb">Pair Correlation Function Analysis of Fluorescence Fluctuations in Big Image Time Series using Python</a>", presented at the Big Data Image Processing & Analysis BigDIPA workshops 2016, 2017, and 2018.<br><br>The <strong>Simulation_Channel.bin</strong> file contains the result of a simulation of fluorescent particles diffusing on a 64x64 grid. The grid contains a diagonal, 300 nm wide channel, which restricts free diffusion. The file was produced using the Globals for Images, SimFCS software. The array shape is (32000, 64, 64), the data type is uint16.<br><br>The <strong>Simulation_Channel.ipcf.bin</strong> file contains the expected results of an ipCF analysis with 32 points at radius 6, and 32 bins. The array shape is (52, 52, 32, 30), the data type is float32.<br><br>The <strong>nih3t3-egfp_2.zip</strong> dataset contains a time series of SPIM images of a biological cell. It consists 35,000 TIFF files of 1024x512 16-bit grayscale samples each, 34.5 GB total.</p>
Integrative analysis of spatial and single-cell transcriptome data from human pancreatic cancer reveals an intermediate cancer cell population associated with poor prognosis_Spatial H&E images
<p>High-resolution H&E images of spatial transcriptome data</p>
CartoCell, a high-content pipeline for accurate 3D image analysis, unveils cell morphology patterns in epithelial cysts.
<p>CartoCell is a deep learning-based image processing pipeline for the high-content segmentation of whole epithelial cysts acquired at low resolution with minimal human intervention. This pipeline enables high-precision cell segmentation that allows a single cell cartography study of major interest for the search of cellular patterns.<br><br>Paper: https://www.cell.com/cell-reports-methods/pdf/S2667-2375(23)00249-7.pdf</p> <h2><strong>Cite this dataset</strong></h2> <h3><strong>Andrés-San Román, J. A., Gordillo-Vázquez, C., Franco-Barranco, D., Morato, L., Fernández-Espartero, C. H., Baonza, G., ... & Escudero, L. M. (2023). CartoCell, a high-content pipeline for 3D image analysis, unveils cell morphology patterns in epithelia. Cell Reports Methods, 3(10). https://doi.org/10.1016/j.crmeth.2023.100597</strong></h3> <p><strong> </strong></p> <div>More info available at: https://data.mendeley.com/datasets/7gbkxgngpm</div>
Data and Codes for: Segmentation uncertainty of vegetated porous media propagates during X-ray CT image-based analysis
<p>Phase segmentation is a crucial step in X-ray computed tomography (CT) for image-based analysis (CT-IBA) to derive soil and root information. How segmentation uncertainty (SU) affects CT-IBA of vegetated soil has never been explored. The enclosed data and codes are used to assist the analysis of SU quantification and propagation in the journal paper published in Plant & Soil. The title of the paper is Segmentation uncertainty of vegetated porous media propagates during X-ray CT image-based analysis. </p>
Data from Imaging and structure analysis of ferroelectric domains, domain walls, and vortices by scanning electron diffraction
<p><strong>Direct electron detectors in scanning transmission electron microscopy give unprecedented possibilities for structure analysis at the nanoscale. In electronic and quantum materials, this new capability gives access to, for example, emergent chiral structures and symmetry-breaking distortions that underpin functional properties. Quantifying nanoscale structural features with statistical significance, however, is complicated by the subtleties of dynamic diffraction and coexisting contrast mechanisms, which often results in low signal-to-noise and the superposition of multiple signals that are challenging to deconvolute. Here we apply scanning electron diffraction to explore local polar distortions in the uniaxial ferroelectric Er(Mn,Ti)O<sub>3</sub>. Using a custom-designed convolutional autoencoder with bespoke regularization, we demonstrate that subtle variations in the scattering signatures of ferroelectric domains, domain walls, and vortex textures can readily be disentangled with statistical significance and separated from extrinsic contributions due to, e.g., variations in specimen thickness or bending. The work demonstrates a pathway to quantitatively measure symmetry-breaking distortions across large areas, mapping structural changes at interfaces and topological structures with nanoscale spatial resolution.</strong></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.