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Dataset results
428 results for “image map”
Targeted Silica Nanoparticles for Real-Time Image-Guided Intraoperative Mapping of Nodal Metastases
ClinicalTrials.gov study NCT02106598. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Three-Dimensional Ultrasonography Versus Magnetic Resonance Imaging for Fibroid Mapping: A Cross Sectional Observational Study
ClinicalTrials.gov study NCT05505331. IPD Sharing: NO. Countries: 1. Publications: 10.
A Study Evaluating Near-infrared Zone II Imaging in Sentinel Lymph Node Mapping in Breast Cancer Patients
ClinicalTrials.gov study NCT05365191. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Axillary Reverse Mapping Using Near-infrared Imaging in Invasive Breast Cancer: Predictors of Nodal Positivity
ClinicalTrials.gov study NCT02994225. IPD Sharing: NO. Countries: 1. Publications: 2.
PCI Suite: Road Map Fusion Imaging in Coronary Diagnostics and Therapy
ClinicalTrials.gov study NCT03074721. IPD Sharing: NO. Countries: 1. Publications: 1.
Learning MRI and Histology Image Mappings for Cancer Diagnosis and Prognosis.
ClinicalTrials.gov study NCT04792138. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Magnetic susceptibility-weighted imaging mapped the migratory route of a paragonimus in brain
Open the record for dataset details and reuse information.
Data from: Early treatment response in non-small cell lung cancer patients using diffusion-weighted imaging and functional diffusion maps - a feasibility study
Open the record for dataset details and reuse information.
Aquarius CAP Level 3 Wind Speed Standard Mapped Image Monthly Data V5.0
Version 5.0 Aquarius CAP Level 3 products are the fourth release of the AQUARIUS/SAC-D mapped salinity and wind speed data based on the Combined Active Passive (CAP) algorithm. CAP Level 3 standard mapped image products contain gridded 1 degree spatial resolution salinity and wind speed data averaged over 7 day and monthly time scales. This particular dataset is the monthly wind speed V5.0 Aquarius CAP product. CAP is a P.I. produced dataset developed and provided by JPL. The CAP algorithm utilizes data from both the onboard radiometer and scatterometer to simultaneously retrieve salinity, wind speed and direction by minimizing the sum of squared differences between model and observations. The main improvements in CAP V5.0 relative to the previous version include: updates to the Geophysical Model Functions to 4th order harmonics with the inclusion of sea surface temperature (SST) and stability at air-sea interface effects; use of the Canadian Meteorological Center (CMC) SST product as the new source ancillary sea surface temperature data in place of NOAA OI SST. The Aquarius instrument is onboard the AQUARIUS/SAC-D satellite, a collaborative effort between NASA and the Argentinian Space Agency Comision Nacional de Actividades Espaciales (CONAE). The instrument consists of three radiometers in push broom alignment at incidence angles of 29, 38, and 46 degrees incidence angles relative to the shadow side of the orbit. Footprints for the beams are: 76 km (along-track) x 94 km (cross-track), 84 km x 120 km and 96km x 156 km, yielding a total cross-track swath of 370 km. The radiometers measure brightness temperature at 1.413 GHz in their respective horizontal and vertical polarizations (TH and TV). A scatterometer operating at 1.26 GHz measures ocean backscatter in each footprint that is used for surface roughness corrections in the estimation of salinity. The scatterometer has an approximate 390km swath.
Aquarius CAP Level 3 Sea Surface Salinity Rain Corrected Standard Mapped Image 7-Day Data V5.0
Version 5.0 Aquarius CAP Level 3 products are the fourth release of the AQUARIUS/SAC-D mapped salinity and wind speed data based on the Combined Active Passive (CAP) algorithm. CAP Level 3 standard mapped image products contain gridded 1 degree spatial resolution salinity and wind speed data averaged over 7 day and monthly time scales. This particular dataset is the 7-Day running mean sea surface salinity (SSS) rain corrected V5.0 Aquarius CAP product. CAP is a P.I. produced dataset developed and provided by JPL. The CAP algorithm utilizes data from both the onboard radiometer and scatterometer to simultaneously retrieve salinity, wind speed and direction by minimizing the sum of squared differences between model and observations. The main improvements in CAP V5.0 relative to the previous version include: updates to the Geophysical Model Functions to 4th order harmonics with the inclusion of sea surface temperature (SST) and stability at air-sea interface effects; use of the Canadian Meteorological Center (CMC) SST product as the new source ancillary sea surface temperature data in place of NOAA OI SST. The Aquarius instrument is onboard the AQUARIUS/SAC-D satellite, a collaborative effort between NASA and the Argentinian Space Agency Comision Nacional de Actividades Espaciales (CONAE). The instrument consists of three radiometers in push broom alignment at incidence angles of 29, 38, and 46 degrees incidence angles relative to the shadow side of the orbit. Footprints for the beams are: 76 km (along-track) x 94 km (cross-track), 84 km x 120 km and 96km x 156 km, yielding a total cross-track swath of 370 km. The radiometers measure brightness temperature at 1.413 GHz in their respective horizontal and vertical polarizations (TH and TV). A scatterometer operating at 1.26 GHz measures ocean backscatter in each footprint that is used for surface roughness corrections in the estimation of salinity. The scatterometer has an approximate 390km swath.
Aquarius CAP Level 3 Sea Surface Salinity Rain Corrected Standard Mapped Image Monthly Data V5.0
Version 5.0 Aquarius CAP Level 3 products are the fourth release of the AQUARIUS/SAC-D mapped salinity and wind speed data based on the Combined Active Passive (CAP) algorithm. CAP Level 3 standard mapped image products contain gridded 1 degree spatial resolution salinity and wind speed data averaged over 7 day and monthly time scales. This particular dataset is the monthly sea surface salinity (SSS) rain corrected V5.0 Aquarius CAP product. CAP is a P.I. produced dataset developed and provided by JPL. The CAP algorithm utilizes data from both the onboard radiometer and scatterometer to simultaneously retrieve salinity, wind speed and direction by minimizing the sum of squared differences between model and observations. The main improvements in CAP V5.0 relative to the previous version include: updates to the Geophysical Model Functions to 4th order harmonics with the inclusion of sea surface temperature (SST) and stability at air-sea interface effects; use of the Canadian Meteorological Center (CMC) SST product as the new source ancillary sea surface temperature data in place of NOAA OI SST. The Aquarius instrument is onboard the AQUARIUS/SAC-D satellite, a collaborative effort between NASA and the Argentinian Space Agency Comision Nacional de Actividades Espaciales (CONAE). The instrument consists of three radiometers in push broom alignment at incidence angles of 29, 38, and 46 degrees incidence angles relative to the shadow side of the orbit. Footprints for the beams are: 76 km (along-track) x 94 km (cross-track), 84 km x 120 km and 96km x 156 km, yielding a total cross-track swath of 370 km. The radiometers measure brightness temperature at 1.413 GHz in their respective horizontal and vertical polarizations (TH and TV). A scatterometer operating at 1.26 GHz measures ocean backscatter in each footprint that is used for surface roughness corrections in the estimation of salinity. The scatterometer has an approximate 390km swath.
Aquarius CAP Level 3 Wind Speed Standard Mapped Image 7-Day Data V5.0
Version 5.0 Aquarius CAP Level 3 products are the fourth release of the AQUARIUS/SAC-D mapped salinity and wind speed data based on the Combined Active Passive (CAP) algorithm. CAP Level 3 standard mapped image products contain gridded 1 degree spatial resolution salinity and wind speed data averaged over 7 day and monthly time scales. This particular dataset is the 7-Day running mean wind speed V5.0 Aquarius CAP product. CAP is a P.I. produced dataset developed and provided by JPL. The CAP algorithm utilizes data from both the onboard radiometer and scatterometer to simultaneously retrieve salinity, wind speed and direction by minimizing the sum of squared differences between model and observations. The main improvements in CAP V5.0 relative to the previous version include: updates to the Geophysical Model Functions to 4th order harmonics with the inclusion of sea surface temperature (SST) and stability at air-sea interface effects; use of the Canadian Meteorological Center (CMC) SST product as the new source ancillary sea surface temperature data in place of NOAA OI SST. The Aquarius instrument is onboard the AQUARIUS/SAC-D satellite, a collaborative effort between NASA and the Argentinian Space Agency Comision Nacional de Actividades Espaciales (CONAE). The instrument consists of three radiometers in push broom alignment at incidence angles of 29, 38, and 46 degrees incidence angles relative to the shadow side of the orbit. Footprints for the beams are: 76 km (along-track) x 94 km (cross-track), 84 km x 120 km and 96km x 156 km, yielding a total cross-track swath of 370 km. The radiometers measure brightness temperature at 1.413 GHz in their respective horizontal and vertical polarizations (TH and TV). A scatterometer operating at 1.26 GHz measures ocean backscatter in each footprint that is used for surface roughness corrections in the estimation of salinity. The scatterometer has an approximate 390km swath.
Aquarius CAP Level 3 Sea Surface Salinity Standard Mapped Image 7-Day Data V5.0
Version 5.0 Aquarius CAP Level 3 products are the fourth release of the AQUARIUS/SAC-D mapped salinity and wind speed data based on the Combined Active Passive (CAP) algorithm. Level 3 standard mapped image products contain gridded 1 degree spatial resolution salinity and wind speed data averaged over 7 day and monthly time scales. This particular dataset is the 7-Day running mean sea surface salinity (SSS) V5.0 Aquarius CAP product. CAP is a P.I. produced dataset developed and provided by JPL. The CAP algorithm utilizes data from both the onboard radiometer and scatterometer to simultaneously retrieve salinity, wind speed and direction by minimizing the sum of squared differences between model and observations. The main improvements in CAP V5.0 relative to the previous version include: updates to the Geophysical Model Functions to 4th order harmonics with the inclusion of sea surface temperature (SST) and stability at air-sea interface effects; use of the Canadian Meteorological Center (CMC) SST product as the new source ancillary sea surface temperature data in place of NOAA OI SST. The Aquarius instrument is onboard the AQUARIUS/SAC-D satellite, a collaborative effort between NASA and the Argentinian Space Agency Comision Nacional de Actividades Espaciales (CONAE). The instrument consists of three radiometers in push broom alignment at incidence angles of 29, 38, and 46 degrees incidence angles relative to the shadow side of the orbit. Footprints for the beams are: 76 km (along-track) x 94 km (cross-track), 84 km x 120 km and 96km x 156 km, yielding a total cross-track swath of 370 km. The radiometers measure brightness temperature at 1.413 GHz in their respective horizontal and vertical polarizations (TH and TV). A scatterometer operating at 1.26 GHz measures ocean backscatter in each footprint that is used for surface roughness corrections in the estimation of salinity. The scatterometer has an approximate 390km swath.
Aquarius CAP Level 3 Sea Surface Salinity Standard Mapped Image Monthly Data V5.0
Version 5.0 Aquarius CAP Level 3 products are the fourth release of the AQUARIUS/SAC-D mapped salinity and wind speed data based on the Combined Active Passive (CAP) algorithm. CAP Level 3 standard mapped image products contain gridded 1 degree spatial resolution salinity and wind speed data averaged over 7 day and monthly time scales. This particular dataset is the monthly sea surface salinity (SSS) V5.0 Aquarius CAP product. CAP is a P.I. produced dataset developed and provided by JPL. The CAP algorithm utilizes data from both the onboard radiometer and scatterometer to simultaneously retrieve salinity, wind speed and direction by minimizing the sum of squared differences between model and observations. The main improvements in CAP V5.0 relative to the previous version include: updates to the Geophysical Model Functions to 4th order harmonics with the inclusion of sea surface temperature (SST) and stability at air-sea interface effects; use of the Canadian Meteorological Center (CMC) SST product as the new source ancillary sea surface temperature data in place of NOAA OI SST. The Aquarius instrument is onboard the AQUARIUS/SAC-D satellite, a collaborative effort between NASA and the Argentinian Space Agency Comision Nacional de Actividades Espaciales (CONAE). The instrument consists of three radiometers in push broom alignment at incidence angles of 29, 38, and 46 degrees incidence angles relative to the shadow side of the orbit. Footprints for the beams are: 76 km (along-track) x 94 km (cross-track), 84 km x 120 km and 96km x 156 km, yielding a total cross-track swath of 370 km. The radiometers measure brightness temperature at 1.413 GHz in their respective horizontal and vertical polarizations (TH and TV). A scatterometer operating at 1.26 GHz measures ocean backscatter in each footprint that is used for surface roughness corrections in the estimation of salinity. The scatterometer has an approximate 390km swath.
A dataset of long-term consistency values of resting-state fMRI connectivity maps in a single individual derived at multiple sites and vendors using the Canadian Dementia Imaging Protocol
<p>This dataset contains preprocessed resting state fMRI data (.nii.gz) with accompanying confound files (.tsv) from the Single Individual volunteer for Multiple Observations across Networks (SIMON; http://fcon_1000.projects.nitrc.org/indi/retro/SIMON.html) dataset that has been minimally preprocessed using the NeuroImaging Analysis Kit (NIAK; http://niak.simexp-lab.org/build/html/PREPROCESSING.html). Preprocessing steps included: (1) Slice timing correction; (2) Estimation of rigid-body motion in fMRI runs, both within- and between sessions; (3) Linear or non-linear coregistration of the structural scan in stereotaxic space; (4) Individual coregistration between structural and functional scans; (5) Resampling of functional scans in stereotaxic space. Confound files (.tsv) have been included for purposes of scrubbing and regression of confounds using NIAK or other analysis software, allowing for further processing without conflicts.</p>
Global color maps of dwarf planet (1) Ceres from Dawn Framing Camera images
<p>These are global maps of dwarf planet (1) Ceres described in "Resolved spectrophotometric properties of the Ceres surface from Dawn Framing Camera images" by <a href="http://dx.doi.org/10.1016/j.icarus.2017.01.026">Schröder <em>et al</em>., Icarus 288 (2017) 201-225</a> (<a href="https://arxiv.org/abs/1701.08550">arXiv</a>). Global color maps created from these data files are shown in Fig. 7 of that paper.</p> <p>These files contain global maps of the photometrically corrected reflectance of the Ceres surface, with one map for each of the 7 narrow-band filter of the Dawn framing camera (FC2). Photometrically corrected reflectance means observed reflectance divided by model reflectance, and the global average of the photometrically corrected reflectance is unity by definition. The model is the Akimov photometric model with parameters valid for global average Ceres and an upper limit of 80° for the photometric angles. The model reflectance was calculated with surface topography derived from a global shape model. Global maps were created as the median of projected individual images of the photometrically corrected reflectance. The IMG and FITS files contain the data in floating point format. The PNG files are provided for visual reference.</p>
Data from: Bi-channel image registration and deep-learning segmentation (BIRDS) for efficient, versatile 3D mapping of mouse brain
<p>We have developed an open-source software called BIRDS (bi-channel image registration and deep-learning segmentation) for the mapping and analysis of 3D microscopy data and applied this to the mouse brain. The BIRDS pipeline includes image pre-processing, bi-channel registration, automatic annotation, creation of a 3D digital frame, high-resolution visualization, and expandable quantitative analysis. This new bi-channel registration algorithm is adaptive to various types of whole-brain data from different microscopy platforms and shows dramatically improved registration accuracy. Additionally, as this platform combines registration with neural networks, its improved function relative to other platforms lies in the fact that the registration procedure can readily provide training data for network construction, while the trained neural network can efficiently segment incomplete/defective brain data that is otherwise difficult to register. Our software is thus optimized to enable either minute-timescale registration-based segmentation of cross-modality, whole-brain datasets or real-time inference-based image segmentation of various brain regions of interest. Jobs can be easily submitted and implemented via a Fiji plugin that can be adapted to most computing environments.</p>
Data from: Geographic Object-Based Image Analysis Framework for Mapping Vegetation Physiognomic Types at Fine Scales in Neotropical Savannas
<p>Spatially-explicit information featuring a wide range of detailed vegetation structural types are necessary to support conservation and ecological analyses. A systematic approach that accurately maps such detailed categories at regional scales is currently lacking for neotropical savannas. We developed a systematic Geographic Object-Based Image Analysis (GEOBIA) framework that accounts for spectral and spatial properties to map Cerrado vegetation structural types at 5-m resolution. This framework counts with a two-step mapping approach: (1) image segmentation and a Random Forest land cover classification based on spectral information (Level 1 classification), followed by (2) a GEOBIA knowledge-based classification that follows contextual and topological spatial rules developed in a systematic manner for mapping Cerrado ecological classes (Level 2 classification).</p><p>The framework was tested for two large study sites covering most major Cerrado physiognomic types: a control site in central Brazil (Taquara watershed site, located in Brasilia, Federal District, and embraces the IBGE Ecological Reserve) and another larger site that is located in an agricultural landscape in the western portion of Bahia State (encompasses parts of the municipalities of: Sao Desiderio, Luis Eduardo Magalhaes, Barreiras, and Riachao das Neves), which brings additional mapping challenges related to intra-class spectral similarity. </p><p>Results demonstrate that our GEOBIA approach is effective for mapping 13 land cover classes with 87.6% overall accuracy, of which all 11 major vegetation classes were identified. For additional details, please check the associated publication with these datasets (Ribeiro et al. 2020).</p><p>The datasets developed in this study are available in shapefile format with attributed metadata following ISO 19115 standards: </p><ul><li><strong>wba_lcmap_geobiaL2_2011lucmask:</strong> final land cover map (Level 2 -- physiognomic types) for a section of the western bahia region in the Cerrado. This product uses a land use mask of 2011 derived from ancillary data</li><li><strong>wba_lcmap_geobiaL2_2013lucmask:</strong> final land cover map (Level 2 -- physiognomic types) for a section of the western bahia region in the Cerrado. This product accounts for the land use mask of 2011 as well as an updated land use mask of 2013 derived from ancillary data</li><li><strong>ibge_taquara_luc_L1_L2_2013_original:</strong> land cover maps (Levels 1 and 2) developed for the Taquara/IBGE site</li><li><strong>ibge_taquara_detailed_luc_2013:</strong> final land cover map (Level 2 -- physiognomic types) developed for the Taquara/IBGE site with additional detailed land use categories</li></ul><p> </p><p><strong>Data</strong></p><p>Mapped land cover classes: 1) cerrado woodland, 2) savanna, 3) open savanna, 4) shrubby grassland, 5) grassland (only present in the Taquara site), 6) cerrado scrub (only present in the western bahia site), 7) marsh, 8) shrub swamp, 9) palm swamp, 10) riparian forest, 11) semi-deciduous forest, 12) seasonally dry tropical forest (only present in the western bahia site), 13) invasive forbes (only present in the Taquara site), 14) non-natural/barren, 15) water, 16) shade, 17) clouds</p><p>The land-use mask incorporated into our maps feature the following classes: main roads, farming/crops, silviculture, and urban areas. </p><p> </p><p><strong>Coordinate Reference System</strong></p><p>Datasets were projected to <strong>South America Albers Equal Area</strong> <strong>Conic</strong>, with all areal calculations based on this projection.</p><p> </p><p><strong>Data Usage</strong> </p><p>The datasets are publicly available and should be cited appropriately (main publication: Ribeiro et al. 2020).</p><p> </p><p><strong>Additional information</strong></p><p>For any other data requests or questions, please contact Fernanda Ribeiro (fernanda.ffr@gmail.com).</p>
Peptide mapping images of Ciona brain
<p>Peptide mapping images of the Ciona cerebral ganglion. GIMP format. </p>
Dataset for "Deep Learning with remote sensing data for image segmentation: example of rice crop mapping using Sentinel-2 images"
<p>Dataset for "Deep Learning with remote sensing data for image segmentation: example of rice crop mapping using Sentinel-2 images". </p> <p> </p> <p>image_prediction_pt1 and _pt2 have the same content as image_prediction.zip but split in two parts for faster downloading with Google Colab (to avoid time out)</p> <p> </p> <p>Contact</p> <p>Ricardo Dalagnol</p> <p>ricds@hotmail.com</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.