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2,001 results for “x-rays”
UK Industrial X-ray CT User-group Benchmark Data: 3D Al target 02
<p>X-ray tomography (CT) image data of a aluminium target as part of the 'UK Industrial X-ray CT User-group Benchmark Study'.<br> <br> The 3D image was generated with an X-ray tomography scan performed by Dr T Lowe at the Manchester X-ray Imaging Facility.<br> <br> The dataset includes: raw radiographs; scan & reconstruction parameter settings file; reconstructed 3D volume. To visualise the 3D volume use software such as ImageJ (https://imagej.net/Fiji/Downloads). The volume image data (.raw) is in binary format and has the following characteristics: 1596 x 1596 x 950; 16-bit Signed; little-endian byte order.</p>
UK Industrial X-ray CT User-group Benchmark Data: 3D Al target 03
<p>X-ray tomography (CT) image data of a aluminium target as part of the 'UK Industrial X-ray CT User-group Benchmark Study'.<br> <br> The 3D image was generated with an X-ray tomography scan performed by Dr T Lowe at the Manchester X-ray Imaging Facility.<br> <br> The dataset includes: raw radiographs; scan & reconstruction parameter settings file; reconstructed 3D volume. To visualise the 3D volume use software such as ImageJ (https://imagej.net/Fiji/Downloads). The volume image data (.raw) is in binary format and has the following characteristics: 1596 x 1596 x 950; 16-bit Signed; little-endian byte order.</p>
UK Industrial X-ray CT User-group Benchmark Data: 3D Al target 07
<p>X-ray tomography (CT) image data of a aluminium target as part of the 'UK Industrial X-ray CT User-group Benchmark Study'.<br> <br> The 3D image was generated with an X-ray tomography scan performed by Dr T Lowe at the Manchester X-ray Imaging Facility.<br> <br> The dataset includes: raw radiographs; scan & reconstruction parameter settings file; reconstructed 3D volume. To visualise the 3D volume use software such as ImageJ (https://imagej.net/Fiji/Downloads). The volume image data (.raw) is in binary format and has the following characteristics: 1596 x 1596 x 950; 16-bit Signed; little-endian byte order.</p>
UK Industrial X-ray CT User-group Benchmark Data: 3D Al target 05
<p>X-ray tomography (CT) image data of a aluminium target as part of the 'UK Industrial X-ray CT User-group Benchmark Study'.<br> <br> The 3D image was generated with an X-ray tomography scan performed by Dr T Lowe at the Manchester X-ray Imaging Facility.<br> <br> The dataset includes: raw radiographs; scan & reconstruction parameter settings file; reconstructed 3D volume. To visualise the 3D volume use software such as ImageJ (https://imagej.net/Fiji/Downloads). The volume image data (.raw) is in binary format and has the following characteristics: 1596 x 1596 x 950; 16-bit Signed; little-endian byte order.</p>
UK Industrial X-ray CT User-group Benchmark Data: 3D Al target 04
<p>X-ray tomography (CT) image data of a aluminium target as part of the 'UK Industrial X-ray CT User-group Benchmark Study'.<br> <br> The 3D image was generated with an X-ray tomography scan performed by Dr T Lowe at the Manchester X-ray Imaging Facility.<br> <br> The dataset includes: raw radiographs; scan & reconstruction parameter settings file; reconstructed 3D volume. To visualise the 3D volume use software such as ImageJ (https://imagej.net/Fiji/Downloads). The volume image data (.raw) is in binary format and has the following characteristics: 1596 x 1596 x 950; 16-bit Signed; little-endian byte order.</p>
UK Industrial X-ray CT User-group Benchmark Data: 3D Al target 09
<p>X-ray tomography (CT) image data of a aluminium target as part of the 'UK Industrial X-ray CT User-group Benchmark Study'.<br> <br> The 3D image was generated with an X-ray tomography scan performed by Dr T Lowe at the Manchester X-ray Imaging Facility.<br> <br> The dataset includes: raw radiographs; scan & reconstruction parameter settings file; reconstructed 3D volume. To visualise the 3D volume use software such as ImageJ (https://imagej.net/Fiji/Downloads). The volume image data (.raw) is in binary format and has the following characteristics: 1596 x 1596 x 950; 16-bit Signed; little-endian byte order.</p>
Chest X-ray images dataset of viral and bacterial pulmonary diseases.
Open the record for dataset details and reuse information.
Dataset to submitted manuscript "Exploring Nanofibrous Networks with X-ray Photon Correlation Spectroscopy"
<p><strong>This zip-archive contains all raw data and processing scripts used to produce the results presented in the manuscript</strong><strong> entitled:</strong></p> <p><strong><em>"Exploring Nanofibrous Networks with X-ray Photon Correlation Spectroscopy"</em></strong></p>
Small-angle X-ray scattering and small-angle X-ray diffraction data for myelin proteolipid protein (PLP) and DM20 with detergent and lipids
<p>Size-exclusion chromatography - small-angle X-ray scattering (SEC-SAXS) data frames for myelin proteolipid protein (PLP) and its shorter form DM20 in complex with <em>n-</em>decyl<em>-</em>β-D<em>-</em>maltopyranoside and small-angle X-ray diffraction data for PLP/DM20 membrane stacks with varying protein-to-lipid ratio and lipid composition collected at EMBL beamline P12, at PETRA-III (Hamburg). </p>
Tomographic datasets for '3d virtual histology of human cerebellum by x-ray phase-contrast tomography'
<p>Tomographic datasets for '3d virtual histology of human cerebellum by x-ray phase-contrast tomography' by M. Töpperwien et al. (PNAS 2018). Reconstructed volumes of both the measurements at the GINIX endstation at PETRAIII (DESY@Hamburg) and the laboratory setup are given. The datasets are saved as .raw in single-precision floating-point format and the size of each dataset is indicated in the filename. Note that in both cases the datasets are those used for the automatic segmentation via the Spherical Hough transform, meaning that for the GINIX dataset the volume was resampled by a factor of 2 and the individual slices were subsequently filtered with a Gaussian with a standard deviation of 0.3 pixels whereas for the laboratory data, the volume was reconstructed at full resolution, followed by a lowpass filtering step.</p> <p>Additionally, the output of the segmentation workflow is given as .dat files, specifying the determined cell positions and radii for both datasets.</p>
Chest x-ray in the COVID-19 pandemic: Radiologists real-world reader performance.
<p>Dataset from the article Cozzi A, Schiaffino S, Arpaia F, Della Pepa G, Tritella S, Bertolotti P, Menicagli L, Monaco CG, Carbonaro LA, Spairani R, Babaei Paskeh B, Sardanelli F. Chest x-ray in the COVID-19 pandemic: Radiologists' real-world reader performance. Eur J Radiol. 2020 Nov;132:109272. doi: 10.1016/j.ejrad.2020.109272. Epub 2020 Sep 10. PMID: 32971326; PMCID: PMC7481070.</p> <p><strong>Abstract</strong></p> <p><strong>Purpose: </strong>To report real-world diagnostic performance of chest x-ray (CXR) readings during the COVID-19 pandemic.</p> <p><strong>Methods: </strong>In this retrospective observational study we enrolled all patients presenting to the emergency department of a Milan-based university hospital from February 24th to April 8th 2020 who underwent nasopharyngeal swab for reverse transcriptase-polymerase chain reaction (RT-PCR) and anteroposterior bedside CXR within 12 h. A composite reference standard combining RT-PCR results with phone-call-based anamnesis was obtained. Radiologists were grouped by CXR reading experience (Group-1, >10 years; Group-2, <10 years), diagnostic performance indexes were calculated for each radiologist and for the two groups.</p> <p><strong>Results: </strong>Group-1 read 435 CXRs (77.0 % disease prevalence): sensitivity was 89.0 %, specificity 66.0 %, accuracy 83.7 %. Group-2 read 100 CXRs (73.0 % prevalence): sensitivity was 89.0 %, specificity 40.7 %, accuracy 76.0 %. During the first half of the outbreak (195 CXRs, 66.7 % disease prevalence), overall sensitivity was 80.8 %, specificity 67.7 %, accuracy 76.4 %, Group-1 sensitivity being similar to Group-2 (80.6 % versus 81.5 %, respectively) but higher specificity (74.0 % versus 46.7 %) and accuracy (78.4 % versus 69.0 %). During the second half (340 CXRs, 81.8 % prevalence), overall sensitivity increased to 92.8 %, specificity dropped to 53.2 %, accuracy increased to 85.6 %, this pattern mirrored in both groups, with decreased specificity (Group-1, 58.0 %; Group-2, 33.3 %) but increased sensitivity (92.7 % and 93.5 %) and accuracy (86.5 % and 81.0 %, respectively).</p> <p><strong>Conclusions: </strong>Real-world CXR diagnostic performance during the COVID-19 pandemic showed overall high sensitivity with higher specificity for more experienced radiologists. The increase in accuracy over time strengthens CXR role as a first line examination in suspected COVID-19 patients.</p>
Masks for hands in X-Ray images
<p>Semantic segmentation masks for hands on scanned X-Rays from the RSNA Bone Age dataset.</p> <p>Mask were obtained manually using thresholding and edge detection and all masks were quality checked.</p> <p>Based on this two models (Tensormask and Efficient-UNet) were trained to obtain the masks on the full RSNA Bone Age dataset.</p> <p> </p>
Abdominal obesity phenotype is associated with COVID-19 chest X-ray severity score better than BMI-based obesity
<p>Malavazos AE, Secchi F, Basilico S, Capitanio G, Boveri S, Milani V, Dubini C, Schiaffino S, Morricone L, Foschini C, Gobbo G, Piccinni R, Saibene A, Sardanelli F, Menicanti L, Guazzi M, Dong C, Romanelli MMC, Carruba M, Iacobellis G. Abdominal obesity phenotype is associated with COVID-19 chest X-ray severity score better than BMI-based obesity. Eat Weight Disord. 2022 Feb;27(1):345-359. doi: 10.1007/s40519-021-01173-w. Epub 2021 Apr 5. PMID: 33821453; PMCID: PMC8020829.</p> <p>Abstract</p> <p><strong>Purpose: </strong>Chest X-ray (CXR) severity score and BMI-based obesity are predictive risk factors for COVID-19 hospital admission. However, the relationship between abdominal obesity and CXR severity score has not yet been fully explored.</p> <p><strong>Methods: </strong>This retrospective cohort study analyzed the association of different adiposity indexes, including waist circumference and body mass index (BMI), with CXR severity score in 215 hospitalized patients with COVID-19.</p> <p><strong>Results: </strong>Patients with abdominal obesity showed significantly higher CXR severity scores and had higher rates of CXR severity scores ≥ 8 compared to those without abdominal obesity (P < 0.001; P = 0.001, respectively). By contrast, patients with normal weight, with overweight and those with BMI-based obesity showed no significant differences in either CXR severity scores or in the rates of CXR severity scores ≥ 8 (P = 0.104; P = 0.271, respectively). Waist circumference and waist-to-height ratio (WHtR) correlated more closely with CXR severity scores than BMI (r = 0.43, P < 0.001; r = 0.41, P < 0.001; r = 0.17, P = 0.012, respectively). The area under the curves (AUCs) for waist circumference and WHtR were significantly higher than that for BMI in identifying a high CXR severity score (≥ 8) (0.68 [0.60-0.75] and 0.67 [0.60-0.74] vs 0.58 [0.51-0.66], P = 0.001). A multivariate analysis indicated abdominal obesity (risk ratio: 1.75, 95% CI: 1.25-2.45, P < 0.001), bronchial asthma (risk ratio: 1.73, 95% CI: 1.07-2.81, P = 0.026) and oxygen saturation at admission (risk ratio: 0.96, 95% CI: 0.94-0.97, P < 0.001) as the only independent factors associated with high CXR severity scores.</p> <p><strong>Conclusion: </strong>Abdominal obesity phenotype is associated with a high CXR severity score better than BMI-based obesity in hospitalized patients with COVID-19. Therefore, when visiting the patient in a hospital setting, waist circumference should be measured, and patients with abdominal obesity should be monitored closely. Level of evidence Cross-sectional descriptive study, Level V.</p> <p> </p>
DATASET RELATED TO ARTICLE " Surface Cranial Ultrasound: The Natural Heir to X-Ray for the Screening of Skull Deformities in Infants"
<p>Dataset contains Clinical data related to subjects involved in the study at title </p>
COVID Moonshot X-ray Data
<p>X-ray crystal structures determined at the XChem facility at Diamond Light Source as part of the COVID Moonshot Consortium</p>
Raw data: X-ray tomography of catalyst H101
<p>XRay tomography data for a bed of spherical catalyst H101.</p><p> </p><p>Funding:</p><p>ProHyGen</p><p>Bundesministerium für Wirtschaft und Klimaschutz</p><p>FKZ 03EI3074B-D</p>
Clenbuterol, X-ray and Tempol treatments on Contusion Rat model
GEO Series GSE5273. Rattus norvegicus. 22 samples. Type: Expression profiling by array.
MER 2 MARS ALPHA PARTICLE X-RAY SPECTROMETER 2 XRAYSPEC V1.0
This archive contains Mars Exploration Rover x-ray data products from the APXS instrument and ancillary files. The APXS x-ray products archived on this volume were generated by the APXS Science Team, Max Planck Institute, for the Mars Exploration Rover Project.
MSL MARS ALPHA PARTICLE X-RAY SPECTROMETER 2 EDR V1.0
Unprocessed experiment data copied from the memory buffer of the APXS instrument aboard the Mars Science Laboratory rover.
ULY JUP GRB SOLAR X-RAY/COSMIC GAMMA-RAY RAW COUNT RATE
The archived data consist of count rates from the sum of two hemispherical detectors covering 4 pi steradians and operating continuously. The detectors are 3 mm thick CsI scintillators coupled to photomultiplier tubes. The nominal energy range is 25-150 keV, but the below table should be consulted to find the accurate thresholds for any day of the mission. A more complete description of the instrument may be found in [HURLEYETAL1992] and [COTINETAL1983]. Although the prime objectives of this investigation are the study of solar and cosmic x- and gamma-ray bursts, it should be noted that the experiment is also sensitive to solar protons and electrons. The former deposit energy directly in the scintillator if they are energetic enough, while the latter may produce x- radiation locally by bremsstrahlung. Thus although the counting rates are generally stable at about 500 c/s over the long term, there are periods of weeks to a month or so when the rates increase considerably due to particles. Examples may be found in March 1991 (solar protons) and February 1992 (particles in the Jovian magnetosphere). The time resolution of the data takes on one of four values depending on the telemetry rate and instrument operating mode: 0.25, 0.5, 1, or 2 seconds.
ScienceDex guides
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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.