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32 results for “chest computed tomography”

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zenodo40/100

Multienergy Fan Beam Computed Tomography Dataset of a Bird Chest Imaged with 3 Different X-ray Spectra

<p><strong>Summary</strong></p> <p>This dataset is a collection of X-ray projection data of a biological imaging phantom (a bird chest) imaged in an X-ray microtomography scanner, using three different X-ray spectra. The dataset also includes a metadata file for each of the scans, specifying the scan geometry and other important scan parameters, as well as photographs and example reconstructions. The dataset is designed for use in algorithm development for multienergy computed tomography.</p> <p>&nbsp;</p> <p><strong>Description</strong></p> <p><em>Sample Information</em></p> <p>The sample is the chest of a common quail (<em>Coturnix coturnix</em>) bird obtained frozen from a local supermarket. The chest section of the frozen bird was removed using a handsaw, and left to melt and settle in a sample holder before imaging.</p> <p><em>Scanner</em></p> <p>The measurement data were acquired using an X-ray microtomography scanner in the University of Helsinki Micro-CT Laboratory. The scanner uses cone beam geometry and it is equipped with an end-window tube with a tungsten target.</p> <p><em>Scan Settings</em></p> <p>The dataset consists of three consecutive scans made using identical geometry but different X-ray spectra and detector exposure times. For each scan, 720 X-ray projections were acquired using an angle increment of 0.5 degrees. Multiple frames were averaged for each projection in order to increase signal-to-noise ratio. The scan geometry and the energy-specific settings are summarized in the following two tables.</p> <p><strong>Table 1.</strong> Imaging geometry used for collecting the data.</p> <table> <tbody> <tr> <td><strong>Parameter</strong></td> <td><strong>Value</strong></td> </tr> <tr> <td>Focus-center distance</td> <td>252 mm</td> </tr> <tr> <td>Focus-detector distance</td> <td>420 mm</td> </tr> <tr> <td>Geometric magnification</td> <td>5/2</td> </tr> <tr> <td>Detector pixel size</td> <td>0.200 mm</td> </tr> <tr> <td>Effective pixel size</td> <td>0.120 mm</td> </tr> <tr> <td>Projection size</td> <td>552 x 576 pixels</td> </tr> <tr> <td>Angular range</td> <td>360'</td> </tr> <tr> <td>#projections</td> <td>720</td> </tr> </tbody> </table> <p><strong>Table 2.</strong> Energy-specific settings used for collecting the data.</p> <table> <tbody> <tr> <td>Energy label</td> <td><em>U</em> (kV)</td> <td>Filtration</td> <td><em>I</em> (&mu;A)</td> <td>Exposure time (ms)</td> <td>Frame averaging</td> </tr> <tr> <td><em>E1</em></td> <td>50</td> <td>None</td> <td>300</td> <td>125</td> <td>4</td> </tr> <tr> <td><em>E2</em></td> <td>80</td> <td>1 mm Al</td> <td>180</td> <td>125</td> <td>4</td> </tr> <tr> <td><em>E3</em></td> <td>120</td> <td>0.5 mm Cu</td> <td>120</td> <td>250</td> <td>4</td> </tr> </tbody> </table> <p><em>Data Post-Processing</em></p> <p>Before the scans were made, a dark current image and flat-field image were acquired for each scan setting. During the scans, dark current subtraction and flat-field correction were automatically applied to the X-ray projections by the measurement software.</p> <p><em>Data Contents</em></p> <p>This dataset contains the following files:</p> <ul> <li>The raw projection data (.tif format) for each scan and a metadata file (.txt format) describing the measurement setup, with formatting that is both human-readable and machine-readable.</li> <li>Pre-created 2D sinograms for each energy level. The sinograms have been created from the central plane of the cone beam, which reduces to fan beam geometry. The sinograms are stored in Matlab's .mat file format in data structures which also contain metadata on the measurement.</li> <li>Photographs taken during the measurement process.</li> <li>Example filtered backprojection (FBP) reconstructions of the central plane of the phantom for each energy. The reconstructions were computed using the &nbsp;Phoenix datos|x CT software provided with the microtomography scanner</li> </ul> <p>&nbsp;</p> <p><strong>Research Group</strong></p> <p>This dataset was produced by the Inverse Problems research group at the Department of Mathematics and Statistics at the University of Helsinki, Finland (<a href="https://www.helsinki.fi/en/researchgroups/inverse-problems">https://www.helsinki.fi/en/researchgroups/inverse-problems</a>) in collaboration with the Computational Physics and Inverse Problems research group at the University of Eastern Finland, Finland (<a href="https://sites.uef.fi/inverse">https://sites.uef.fi/inverse</a>) and the X-ray Laboratory at the Department of Physics at the University of Helsinki, Finland (<a href="https://www.helsinki.fi/en/researchgroups/x-ray-laboratory">https://www.helsinki.fi/en/researchgroups/x-ray-laboratory</a>).</p> <p>&nbsp;</p> <p><strong>Previous Use</strong></p> <p>This dataset has been used in the following publications:</p> <p>Jussi Toivanen, Alexander Meaney, Samuli Siltanen, Ville Kolehmainen. Joint reconstruction in low dose multi-energy CT.&nbsp;<em>Inverse Problems and Imaging</em>, 2020, 14(4): 607-629.&nbsp;doi:&nbsp;<a href="https://doi.org/10.3934/ipi.2020028" target="_blank" rel="noopener">10.3934/ipi.2020028</a>.</p> <p>E. Cueva, A. Meaney, S. Siltanen, M. J. Ehrhardt. Synergistic multi-spectral CT reconstruction with directional total variation. <em>Philos Trans A Math Phys Eng Sci</em>. 2021 Aug 23;379(2204):20200198. doi: <a href="https://doi.org/10.1098/rsta.2020.0198">10.1098/rsta.2020.0198</a>.</p> <p>&nbsp;</p> <p><strong>Additional Links</strong></p> <p>To get started with the data, we recommend looking at the HelTomo toolbox, specifically created for working with CBCT data collected by the Inverse Problems research group, and available at&nbsp;<a href="https://se.mathworks.com/matlabcentral/fileexchange/74417-heltomo-helsinki-tomography-toolbox">https://se.mathworks.com/matlabcentral/fileexchange/74417-heltomo-helsinki-tomography-toolbox</a>.</p> <p>&nbsp;</p> <p><strong>Acknowledgements</strong></p> <p>We wish to thank laboratory engineer Heikki Suhonen for his guidance and assistance in conducting the measurements.</p> <p>&nbsp;</p> <p><strong>Contact Details</strong></p> <p>For more information or guidance in using these datasets, please contact alexander.meaney [at] helsinki.fi.</p>

opencc-by-4.0May 2024View details →
zenodo36/100

The impact of deep learning aid on the workload and interpretation accuracy of radiologists on chest computed tomography: a cross-over reader study.

<p>Data used to perform statistical analysis in "The impact of deep learning aid on the workload and interpretation accuracy of radiologists on chest computed tomography: a cross-over reader study.".&nbsp;</p>

opencc-by-4.0Apr 2024View details →
zenodo32/100

Coronavirus Disease 2019 (COVID-19) in Italy: features on Chest Computed Tomography using a structured report system

<p>We uploaded a dataset including the presence of GGO and its distribution for each patient presented in the manuscript:&nbsp;Grassi R, Fusco R, Belfiore MP, Montanelli A, Patelli G, Urraro F, Petrillo A, Granata V, Sacco P, Mazzei MA, Feragalli B, Reginelli A, Cappabianca S. Coronavirus disease 2019 (COVID-19) in Italy: features on chest computed tomography using a structured report system. Sci Rep. 2020 Oct 14;10(1):17236. doi: 10.1038/s41598-020-73788-5. Erratum in: Sci Rep. 2021 Feb 15;11(1):4231. PMID: 33057039; PMCID: PMC7566610.</p>

opencc-by-4.0Feb 2021View details →
ClinicalTrials.gov32/100

Coronary Computed Tomography for Systematic Triage of Acute Chest Pain Patients to Treatment (CT-STAT)

ClinicalTrials.gov study NCT00468325. IPD Sharing: Not stated. Countries: 1. Publications: 1.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov32/100

Better Evaluation of Acute Chest Pain With Computed Tomography Angiography

ClinicalTrials.gov study NCT01413282. IPD Sharing: NO. Countries: 1. Publications: 1.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov32/100

Fractional Flow Reserve Derived From Computed Tomography Coronary Angiography in the Assessment and Management of Stable Chest Pain

ClinicalTrials.gov study NCT03187639. IPD Sharing: NO. Countries: 1. Publications: 1.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov32/100

Study of Coronary Artery Computed Tomography to Diagnose Emergency Chest Pain

ClinicalTrials.gov study NCT00273832. IPD Sharing: Not stated. Countries: 1. Publications: 5.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov32/100

Stress Echocardiography and Heart Computed Tomography (CT) Scan in Emergency Department Patients With Chest Pain

ClinicalTrials.gov study NCT01384448. IPD Sharing: Not stated. Countries: 1. Publications: 2.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov32/100

ECG-less Coronary Computed Tomography Angiography in the Management of Patients Presenting With High-troponin Chest Pain

ClinicalTrials.gov study NCT07192965. IPD Sharing: Not stated. Countries: 1. Publications: 14.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov32/100

Troponin in Acute Chest Pain to Risk Stratify and Guide EffecTive Use of Computed Tomography Coronary Angiography

ClinicalTrials.gov study NCT03952351. IPD Sharing: YES. Countries: 1. Publications: 1.

controlledIPD-YESFeb 2026View details →
ClinicalTrials.gov32/100

A Study of Computed Tomography (CT) for Evaluation of Coronary Artery Blockages in Typical or Atypical Chest Pain

ClinicalTrials.gov study NCT00348569. IPD Sharing: Not stated. Countries: 1. Publications: 2.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov28/100

Myocardial Stress Perfusion Computed Tomography in the Evaluation of Patients With Acute Chest Pain Using a Novel 3rd Generation Dual-source CT System

ClinicalTrials.gov study NCT02308475. IPD Sharing: Not stated. Countries: 1. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov28/100

Low-Dose Chest Computed Tomography Screening for Lung Cancer in Survivors of Hodgkin's Disease

ClinicalTrials.gov study NCT00601146. IPD Sharing: NO. Countries: 1. Publications: 0.

closedIPD-NOFeb 2026View details →
dryad28/100

Data from: Improving early diagnosis of pulmonary infections in patients with febrile neutropenia using low-dose chest computed tomography

Open the record for dataset details and reuse information.

publicFeb 2018View details →
dryad24/100

Data from: Birt-Hogg-Dube syndrome prospectively detected by review of chest computed tomography scans

Purpose: Birt-Hogg-Dube syndrome (BHD) is a rare disorder caused by mutations in the gene that encodes folliculin (FLCN) and is inherited in an autosomal dominant manner. BHD is commonly accompanied by fibrofolliculomas, renal tumors, multiple pulmonary cysts, and spontaneous pneumothorax. The aim of this study was to detect BHD prospectively in patients undergoing chest computed tomography (CT) scans and to evaluate further the characteristics of BHD in Korea. Methods: We prospectively checked and reviewed the chest CT scans obtained for 10,883 patients at Gangnam Severance Hospital, Seoul, Korea, from June 1, 2015 to May 31, 2016. Seventeen patients met the study inclusion criteria and underwent screening for FLCN mutation to confirm BHD. We analyzed the characteristics of the patients confirmed to have BHD and those for a further 6 patients who had previously been described in Korea. Results: Six (0.06%) of the 10,883 patients reviewed were diagnosed with BHD. There was no difference in demographic or clinical features between the patients with BHD (n=6) and those without BHD (n=11). Pneumothorax was present in 50% of the patients with BHD but typical skin and renal lesions were absent. The maximum size of the cysts in the BHD group (median 39.4 mm; interquartile range [IQR] 11.4 mm) was significantly larger than that in the non-BHD group (median 15.8 mm; IQR 7.8 mm; P = 0.001). Variable morphology was seen in 100.0% of the cysts in the BHD group but in only 18.2% of the cysts in the non-BHD group (P = 0.002). Nine (95%) of the total of 12 Korean patients with BHD had experienced pneumothorax. Typical skin and renal lesions were present in 20.0% of patients with BHD. Conclusions: Our findings suggest that BHD can be detected if chest CT scans are read in detail.

opencc-zeroDec 2016View details →
ClinicalTrials.gov24/100

Chest Computed Tomography (CT) Screening Study With Antibody Testing

ClinicalTrials.gov study NCT01203579. IPD Sharing: Not stated. Countries: 1. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov24/100

Influence of Tracheal-bronchial Anatomy Changes on Multi-detector Computed Tomography Scan of the Chest Upon Placement of Left-Sided Double Lumen Endotracheal Tube

ClinicalTrials.gov study NCT03838653. IPD Sharing: YES. Countries: 1. Publications: 0.

controlledIPD-YESFeb 2026View details →
ClinicalTrials.gov24/100

Natural History of Coronary Atherosclerosis in Real-World Stable Chest Pain Patients Underwent Computed Tomography Angiography in Comparison With Invasive Multimodality Imaging

ClinicalTrials.gov study NCT02440646. IPD Sharing: UNDECIDED. Countries: 3. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov24/100

High-Sensitivity Troponin T and Coronary Computed Tomography Angiography for Rapid Diagnosis of Emergency Chest Pain

ClinicalTrials.gov study NCT01836211. IPD Sharing: Not stated. Countries: 1. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov24/100

Computed Tomography in Detecting Movement of the Esophagus in Patients Undergoing Radiation Therapy to the Chest

ClinicalTrials.gov study NCT00433524. IPD Sharing: Not stated. Countries: 1. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →

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