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2,007
datasets available to search
ShareScore release 0.9.0
Dataset results
2,007 results for “Image Studies”
Pilot Study to Evaluate High Resolution PET Image-Guidance for Sampling of Breast Abnormalities
ClinicalTrials.gov study NCT00606931. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Data from: Thalamus and focal to bilateral seizures: a multi-scale cognitive imaging study
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Anatomical, behavioral, and imaging data for a study on neural circuits for stress modulation of pain
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Semi-Siamese U-Net for separation of lung and heart bioimpedance images: a simulation study of thorax EIT
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Three-ball cascade juggling as a new paradigm to study complex motor execution using mobile brain-body imaging (EEG)
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Dual‐fluorescence imaging and automated trophallaxis detection for studying multi‐nutrient regulation in superorganisms
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Health sciences librarians’ awareness and incorporation of informed consent standards for medical image publication: A preliminary study
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Combining CRISPR/Cas9 and brain imaging to study the link from genes to molecules to networks
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LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study collected on 1982-11-18
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study, originally collected on 1982-11-18 (15:14:41.5130630Z) by Landsat 4, row 33, path 15. Cloud cover was 30 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT40150331982322XXX01, LPGS_12.0.2, USGS, Sioux Falls, 2012-07-12T15:15:58Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study collected on 1983-01-21
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study, originally collected on 1983-01-21 (15:15:35.2090380Z) by Landsat 4, row 33, path 15. Cloud cover was 30 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT40150331983021XXX04, LPGS_12.0.2, USGS, Sioux Falls, 2012-07-12T15:17:09Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study collected on 1987-06-25
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study, originally collected on 1987-06-25 (15:05:09.9260560Z) by Landsat 4, row 33, path 15. Cloud cover was 0 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT40150331987176XXX06, LPGS_12.0.2, USGS, Sioux Falls, 2012-05-30T17:21:44Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study collected on 1987-07-11
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study, originally collected on 1987-07-11 (15:04:59.2290750Z) by Landsat 4, row 33, path 15. Cloud cover was 10 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT40150331987192XXX02, LPGS_12.0.2, USGS, Sioux Falls, 2012-07-12T15:17:23Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study collected on 1984-03-24
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study, originally collected on 1984-03-24 (15:11:29.6240690Z) by Landsat 5, row 33, path 15. Cloud cover was 10 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT50150331984084XXX18, LPGS_12.0.2, USGS, Sioux Falls, 2012-05-03T02:55:41Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study collected on 1984-06-08
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study, originally collected on 1984-06-08 (15:14:38.5230940Z) by Landsat 5, row 33, path 15. Cloud cover was 30 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT50150331984160XXX17, LPGS_12.0.2, USGS, Sioux Falls, 2012-04-23T05:54:16Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study collected on 1984-08-27
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study, originally collected on 1984-08-27 (15:16:29.0100250Z) by Landsat 5, row 33, path 15. Cloud cover was 0 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT50150331984240XXX10, LPGS_12.0.0, USGS, Sioux Falls, 2012-03-28T10:56:49Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study collected on 1984-10-14
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study, originally collected on 1984-10-14 (15:16:31.9050940Z) by Landsat 5, row 33, path 15. Cloud cover was 35.21 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT50150331984288PAC00, LPGS_12.0.2, USGS, Sioux Falls, 2012-07-12T15:13:39Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study collected on 1984-12-01
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study, originally collected on 1984-12-01 (15:16:22.6110310Z) by Landsat 5, row 33, path 15. Cloud cover was 0 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT50150331984336XXX07, LPGS_12.0.2, USGS, Sioux Falls, 2012-05-30T17:22:46Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study collected on 1984-12-17
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study, originally collected on 1984-12-17 (15:16:33.9990380Z) by Landsat 5, row 33, path 15. Cloud cover was 40 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT50150331984352XXX04, LPGS_12.0.2, USGS, Sioux Falls, 2012-07-12T15:14:30Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study collected on 1985-02-03
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study, originally collected on 1985-02-03 (15:16:51.9300000Z) by Landsat 5, row 33, path 15. Cloud cover was 10 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT50150331985034XXX12, LPGS_12.0.2, USGS, Sioux Falls, 2012-07-12T15:13:31Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study collected on 1985-04-08
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study, originally collected on 1985-04-08 (15:16:47.2740060Z) by Landsat 5, row 33, path 15. Cloud cover was 50 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT50150331985098XXX03, LPGS_12.0.2, USGS, Sioux Falls, 2012-07-12T15:40:07Z.
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.