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300 results for “Echo”
Stress Echo 2030: the Novel ABCDE-(FGLPR) Protocol to Define the Future of Imaging
ClinicalTrials.gov study NCT05081115. IPD Sharing: Not stated. Countries: 1. Publications: 27.
A Prospective Randomized Multicenter Trial of the Guidewire for Echo-guided Interventions
ClinicalTrials.gov study NCT04096924. IPD Sharing: NO. Countries: 1. Publications: 1.
The CT-verified Data Collection Study to Investigate the Correlation Between the Leadless Pacemaker Tip Location and Echo, ECG
ClinicalTrials.gov study NCT06910059. IPD Sharing: NO. Countries: 1. Publications: 3.
Data from: Quantitative ornithology with a commercial marine radar: standard-target calibration, target detection and tracking, and measurement of echoes from individuals and flocks
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Data from: Echoes of a distant time: effects of historical processes on contemporary genetic patterns in Galaxias platei in Patagonia
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Data from: Acoustic emissions of Sorex unguiculatus (Mammalia: Soricidae): assessing the echo-based orientation hypothesis
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The long-range echo scene of the sperm whale biosonar
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SWOT 2019-2020 Prelaunch Oceanography Field Campaign SIO Pressure-sensing Inverted Echo Sounder (PIES)
This dataset provides the in-situ measurements from a Pressure-sensing Inverted Echo Sounder (PIES) deployed by the SWOT prelaunch field campaign. The campaign was designed to test the performance of several instruments/platforms in meeting the SWOT Calibration/Validation (CalVal) requirement. It was conducted near the SWOT CalVal crossover location, about 300 kilometers west of Monterey, California between September, 2019 and January, 2020. The campaign also deployed three CTD moorings, a slocum glider, and another bottom pressure recorder. The PIES measurements include bottom pressure and the round-trip travel time from the IES, which can be used to derive equivalent steric height through regression. Details can be found in the user guide and the journal reference given in the documentation section.
The bright ultra-short echo time MRI signal seen at the osteochondral junction is not located in the calcified cartilage.
<p>The raw data for the article</p> <p><strong>The bright ultra-short echo time SWIFT MRI signal at the osteochondral junction is not located in the calcified cartilage</strong></p> <p> </p> <p><sup>1</sup>Olli Nykänen (M.Sc.), <sup>1</sup>Henri P.P. Leskinen (M.Sc.), <sup>1,2</sup>Mikko Finnilä (Ph.D.), <sup>2,6</sup>Sakari S. Karhula, (Ph.D.)<sup> 1,3</sup>Mikael J. Turunen (Ph.D.), <sup>1,4,5</sup>Juha Töyräs (Ph.D.), <sup>2,6</sup>Simo Saarakkala (Ph.D.), <sup>1,2</sup>Mikko J. Nissi (Ph.D.)</p> <p> </p> <p>1. Department of Applied Physics, University of Eastern Finland, Kuopio, Finland</p> <p>2. Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland</p> <p>3. SIBlabs, University of Eastern Finland, Kuopio, Finland</p> <p>4. Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland</p> <p>5. School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia</p> <p>6. Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland</p> <p>Accepted for publication in Journal of Orthopaedic Research</p> <p> </p>
Data from: Validation of perfusion quantification with 3D gradient echo dynamic contrast-enhanced magnetic resonance imaging using a blood pool contrast agent in skeletal swine muscle
The purpose of our study was to validate perfusion quantification in a low-perfused tissue by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) with shared k-space sampling using a blood pool contrast agent. Perfusion measurements were performed in a total of seven female pigs. An ultrasonic Doppler probe was attached to the right femoral artery to determine total flow in the hind leg musculature. The femoral artery was catheterized for continuous local administration of adenosine to increase blood flow up to four times the baseline level. Three different stable perfusion levels were induced. The MR protocol included a 3D gradient-echo sequence with a temporal resolution of approximately 1.5 seconds. Before each dynamic sequence, static MR images were acquired with flip angles of 5°, 10°, 20°, and 30°. Both static and dynamic images were used to generate relaxation rate and baseline magnetization maps with a flip angle method. 0.1 mL/kg body weight of blood pool contrast medium was injected via a central venous catheter at a flow rate of 5 mL/s. The right hind leg was segmented in 3D into medial, cranial, lateral, and pelvic thigh muscles, lower leg, bones, skin, and fat. The arterial input function (AIF) was measured in the aorta. Perfusion of the different anatomic regions was calculated using a one- and a two-compartment model with delay- and dispersion-corrected AIFs. The F-test for model comparison was used to decide whether to use the results of the one- or two-compartment model fit. Total flow was calculated by integrating volume-weighted perfusion values over the whole measured region. The resulting values of delay, dispersion, blood volume, mean transit time, and flow were all in physiologically and physically reasonable ranges. In 107 of 160 ROIs, the blood signal was separated, using a two-compartment model, into a capillary and an arteriolar signal contribution, decided by the F-test. Overall flow in hind leg muscles, as measured by the ultrasound probe, highly correlated with total flow determined by MRI, R = 0.89 and P = 10−7. Linear regression yielded a slope of 1.2 and a y-axis intercept of 259 mL/min. The mean total volume of the investigated muscle tissue corresponds to an offset perfusion of 4.7mL/(min ⋅ 100cm3). The DCE-MRI technique presented here uses a blood pool contrast medium in combination with a two-compartment tracer kinetic model and allows absolute quantification of low-perfused non-cerebral organs such as muscles.
FIGURE 11 in A description of Echo perornata spec. nov. from Xizang (Tibet), China (Odonata: Calopterygidae)
FIGURE 11. Wings of Echo m. margarita male specimen from Khasia Hills, Meghalaya, India.
FIGURES 3-4 in A description of Echo perornata spec. nov. from Xizang (Tibet), China (Odonata: Calopterygidae)
FIGURES 3-4. Echo perornata spec. nov.; 3) wings of holotype male; 4) wings of paratype female.
FIGURES 1–2 in A description of Echo perornata spec. nov. from Xizang (Tibet), China (Odonata: Calopterygidae)
FIGURES 1–2. Echo perornata spec. nov.; 1) habitus of holotype male; 2) habitus of paratype female.
Data for: Free-Breathing Liver Fat, R2* and B0 Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction (Part 4/5)
<p>This data set consists of MRI measurement data for liver scans acquired with a 3D stack-of-stars multi-echo FLASH sequence during free breathing as described in:</p> <p>Zhengguo Tan, Christina Unterberg-Buchwald, Moritz Blumenthal, Nick Scholand, Philip Schaten, Christian Holme, Xiaoqing Wang, Dirk Raddatz, Martin Uecker. <a href="https://doi.org/10.1109/TMI.2022.3228075">Free-Breathing Liver Fat, R2* and B0 Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction.</a> IEEE Transactions on Medical Imaging 42:1374-1387 (2023) </p> <p>The data stored in the format of the BART toolbox (DOI: 10.5281/zenodo.592960).</p>
Data for: Free-Breathing Liver Fat, R2* and B0 Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction (Part 5/5)
<p>This data set consists of MRI measurement data for liver scans acquired with a 3D stack-of-stars multi-echo FLASH sequence during free breathing as described in:</p> <p>Zhengguo Tan, Christina Unterberg-Buchwald, Moritz Blumenthal, Nick Scholand, Philip Schaten, Christian Holme, Xiaoqing Wang, Dirk Raddatz, Martin Uecker. <a href="https://doi.org/10.1109/TMI.2022.3228075">Free-Breathing Liver Fat, R2* and B0 Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction.</a> IEEE Transactions on Medical Imaging 42:1374-1387 (2023) </p> <p>The data stored in the format of the BART toolbox (DOI: 10.5281/zenodo.592960).</p>
Data for: Free-Breathing Liver Fat, R2* and B0 Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction (Part 3/5)
<p>This data set consists of MRI measurement data for liver scans acquired with a 3D stack-of-stars multi-echo FLASH sequence during free breathing as described in:</p> <p>Zhengguo Tan, Christina Unterberg-Buchwald, Moritz Blumenthal, Nick Scholand, Philip Schaten, Christian Holme, Xiaoqing Wang, Dirk Raddatz, Martin Uecker. <a href="https://doi.org/10.1109/TMI.2022.3228075">Free-Breathing Liver Fat, R2* and B0 Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction.</a> IEEE Transactions on Medical Imaging 42:1374-1387 (2023) </p> <p>The data stored in the format of the BART toolbox (DOI: 10.5281/zenodo.592960).</p>
Data for: Free-Breathing Liver Fat, R2* and B0 Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction (Part 1/5)
<p>This data set consists of MRI measurement data for liver scans acquired with a 3D stack-of-stars multi-echo FLASH sequence during free breathing as described in:</p> <p>Zhengguo Tan, Christina Unterberg-Buchwald, Moritz Blumenthal, Nick Scholand, Philip Schaten, Christian Holme, Xiaoqing Wang, Dirk Raddatz, Martin Uecker. <a href="https://doi.org/10.1109/TMI.2022.3228075">Free-Breathing Liver Fat, R2* and B0 Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction.</a> IEEE Transactions on Medical Imaging 42:1374-1387 (2023) </p> <p>The data stored in the format of the BART toolbox (DOI: 10.5281/zenodo.592960).</p>
Data for: Free-Breathing Liver Fat, R2* and B0 Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction (Part 2/5)
<p>This data set consists of MRI measurement data for liver scans acquired with a 3D stack-of-stars multi-echo FLASH sequence during free breathing as described in:</p> <p>Zhengguo Tan, Christina Unterberg-Buchwald, Moritz Blumenthal, Nick Scholand, Philip Schaten, Christian Holme, Xiaoqing Wang, Dirk Raddatz, Martin Uecker. <a href="https://doi.org/10.1109/TMI.2022.3228075">Free-Breathing Liver Fat, R2* and B0 Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction.</a> IEEE Transactions on Medical Imaging 42:1374-1387 (2023) </p> <p>The data stored in the format of the BART toolbox (DOI: 10.5281/zenodo.592960).</p>
Supporting Data for "Spin-echo small-angle neutron scattering (SESANS) studies of diblock copolymer nanoparticles" (Soft Matter, doi:10.1039/c8sm01425f)
<p>SAXS [Q / Å^{-1}, I(Q) / Arb. unit, error I(Q) / Arb. unit] data as *.dat files</p> <p>SESANS [Columns labeled] data as *.ses files</p>
A Study of the Safety, Tolerability, and Efficacy of Epacadostat Administered in Combination With Nivolumab in Select Advanced Cancers (ECHO-204)
ClinicalTrials.gov study NCT02327078. IPD Sharing: Not stated. Countries: 2. Publications: 0.
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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.