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755 results for “Angiography”
ARCADE: Automatic Region-based Coronary Artery Disease diagnostics using x-ray angiography imagEs Dataset
<p>ARCADE: Automatic Region-based Coronary Artery Disease diagnostics using x-ray angiography imagEs Dataset Phase 2 consist of two folders with 300 images in each of them as well as annotations. </p> <p>ARCADE: Automatic Region-based Coronary Artery Disease diagnostics using x-ray angiography imagEs Dataset Phase 1 consists of two datasets of XCA images for each of two tasks of ARCADE challenge. The first task includes in total 1200 coronary vessel tree images, which are divided into train(1000) and validation(200) groups, images for training are followed with annotations, depicting the division of a heart into 26 different regions based on the Syntax Score methodology[1]. Similarly, the second task includes a different set of 1200 images with same train-val division proportion with annotated regions containing atherosclerotic plaques. This dataset, carefully annotated by medical experts, enables scientists to actively contribute towards the advancement of an automated risk assessment system for patients with CAD. </p> <p>The dataset structure is as follows: top-level directories "syntax" and "stenosis" contain files for the two dataset objectives, namely: i) vessel branch classification according to the SYNTAX methodology; and ii) stenosis detection. Inside both directories, there are 3 subsets of the dataset, such as "train", "val", and "test". Inside each of those folders, there are 2 lower-level directories - "images", and "annotations". Inside the "images" folder there are images in ".png" format, extracted from DICOM recordings. The "annotations" folders contain single ".JSON" files, which are named in correspondence to the objective, i.e. "train.JSON", "val.JSON", and "test.JSON".</p> <p>The structure of ".JSON" contains three top-level fields: "images", "categories", and "annotations". The "images" field contains the unique "id" of the image in the dataset, its "width" and "height" in pixels, and the "file_name" sub-field, which contains specific information about the image. The "categories" field contains a unique "id" from 1 to 26, and a "name", relating it to the SYNTAX descriptions. The "annotations" field contains a unique "id" of the annotation, "image_id" value, relating it to the specific image from the "images" field, and a "category_id" relating it to the specific category from the "categories" field. The "segmentation" sub-field contains coordinates of mask edge points in "XYXY" format. Bounding box coordinates are given in the "bbox" field in the "XYWH" format, where the first 2 values represent the x and y coordinates of the left-most and top-most points in the segmentation mask. The height and width of the bounding box are determined by the difference between the right-most and bottom-most points and the first two values. Finally, the "area" field provides the total area of the bounding box, calculated as the area of a rectangle.</p> <p> </p> <p>The corresponding Dataset Article will be provided later. </p> <p>[1] Syntax score segment definitions. https://syntaxscore.org/index.php/tutorial/definitions/14-appendix-i-segment-definitions</p>
Time-encoded pseudo-continuous arterial spin labeling: increasing SNR in ASL dynamic angiography
<p>This repository contains the raw K-space data and all MATLAB (The MathWorks, Natick, MA) code used for reconstruction, simulations, data analysis, and figure generation used in the article titled "Time-encoded pseudo-continuous arterial spin labeling: increasing SNR in ASL dynamic angiography".</p> <p>## Referencing</p> <p>If you use any of the data or the code provided here, please cite:</p> <p>1. Woods JG, Schauman SS, Chiew M, Chappell MA, Okell TW. Time-encoded pseudo-continuous arterial spin labeling: Increasing SNR in ASL dynamic angiography. Magnetic Resonance in Medicine. 2023; doi:10.1002/mrm.29491<br> 2. This Zenodo repository: Joseph G. Woods, S. Sophie Schauman, Mark Chiew, Michael A. Chappell & Thomas W. Okell. (2022). Time-encoded pseudo-continuous arterial spin labeling: increasing SNR in ASL dynamic angiography [Data set]. Zenodo. https://doi.org/10.5281/zenodo.6791097</p> <p> </p> <p>If you use the reconstruction code provided here, please also cite:</p> <p>1. Fessler JA, Sutton BP. Nonuniform fast fourier transforms using min-max interpolation. IEEE Transactions on Signal Processing. 2003;51(2):560-574. doi:10.1109/TSP.2002.807005<br> 2. Fessler JA. Michigan Image Reconstruction Toolbox. https://web.eecs.umich.edu/~fessler/code/. Accessed February 26, 2018.<br> 3. Schauman SS. Accelerated_TEASL. https://github.com/SophieSchau/Accelerated_TEASL. Accessed October 19, 2020.<br> 4. Chiew M. MR Linear Encoding Operators. https://users.fmrib.ox.ac.uk/~mchiew/Tools.html. Accessed March 30, 2020.</p> <p>## Notes for use:</p> <p>All data processing is performed in MATLAB (tested with 2021a and 2021b on macOS 10.14 (Mojave) and 12 (Monterey))</p> <p>The "code/" and "data/" folders should be placed within the same folder. The necessary file paths within each script in "code/" will be set up automatically.</p> <p>**Note**: the file paths use "/", so would need to be manually changed for use on Windows, which uses "\" in file paths.</p> <p>- For performing full reconstruction of in vivo K-space data, **run reconalldata.m**.<br> - All code provided<br> - Uses:<br> 1. Jeff Fessler's MIRT: http://web.eecs.umich.edu/~fessler/irt/fessler.tgz<br> 2. Mark Chiew's: xfm_NUFFT.m, etc: https://users.fmrib.ox.ac.uk/~mchiew/Tools.html<br> 3. Sophie Schauman's Accelerated_TEASL: https://github.com/SophieSchau/Accelerated_TEASL</p> <p>- For plotting in-vivo data, **run figures_invivo.m**.<br> - FSL's read_avw to read in NIFTIs (but can replace this with MATLAB's in-built niftiread instead).<br> - (Install FSL from here: https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FslInstallation)<br> - All other code provided</p> <p>- For performing simulation and plotting results, **run figures_simulation.m**.<br> - All code provided</p> <p>- Location of specific Figure generation code:<br> - Figure 1: no code - manually made.<br> - Figure 2: figures_invivo.m<br> - Figure 3: figures_simulation.m<br> - Figure 4: figures_invivo.m<br> - Figure 5: figures_invivo.m<br> - Figure 6: figures_invivo.m<br> - Figure 7: figures_invivo.m<br> - Figure 8: figures_invivo.m<br> - Figure 9: figures_simulation.m<br> - Figure 10: figures_invivo.m<br> - Supporting Information Figure S1: figures_simulation.m<br> - Supporting Information Figure S2: figures_invivo.m<br> - Supporting Information Figure S3: figures_invivo.m<br> - Supporting Information Figure S4: figures_invivo.m<br> - Supporting Information Figure S5: figures_invivo.m<br> - Supporting Information Figure S6: figures_invivo.m<br> - Supporting Information Figure S7: figures_invivo.m<br> - Supporting Information Figure S8: figures_invivo.m<br> - Supporting Information Figure S9: figures_invivo.m<br> - Supporting Information Figure S10: figures_simulation.m</p>
SYNTAX III REVOLUTION Trial: A Randomized Study Investigating the Use of CT Scan and Angiography of the Heart to Help the Doctors Decide Which Method is the Best to Improve Blood Supply to the Heart i
ClinicalTrials.gov study NCT02813473. IPD Sharing: YES. Countries: 5. Publications: 2.
Multiple Sclerosis: Cerebral Circulation Time is prolonged and not correlated with expanded disability status scale (EDSS). A study using digital subtracted angiography
<p>Dataset used to study the relationship between cerebral circulation time (CCT) and some clinical evidences, e.g. expand disability status scale (EDSS), disease duration, age at onset,... CCT was measured through the digital subtraction angiography (DSA) technique. </p> <p>Statistical Parametric Mapping software (SPM, Wellcome Department of Cognitive Neurology, Institute of Neurology, University College London; http://www.fil.ion.ucl.ac.uk/spm/) and ad-hoc scripts developed in the MATLAB scientific computing environment (http://www.mathworks.com, MathWorks, MA, USA) were applied to valuate the lesion volume and brain volume in MS patients.</p>
Plane wave ultrasound and OCT angiography of the eye in preeclampsia
<p>This study involves examination of ocular blood flow in human subjects in preeclampsia (PE). Both eyes were examined by plane-wave ultrasound and by optical coherence angiography (OCTA) within 72 hours of delivery. Ultrasound Doppler was used to assess flow velocity and resistance in the central retinal artery and vein, the short posterior ciliary arteries and the choroid. OCTA was used to assess vascular density in the superficial and deep retina and the choriocapillaris. Analysis included correlation with blood pressure, assessment of differences between normal and PE and correlation of ultrasound Doppler with OCTA vascular density.</p>
Repository for "Standardized classification of cerebral vasospasm after subarachnoid hemorrhage by digital subtraction angiography"
<p>Repositories for "Standardized classification of cerebral vasospasm after subarachnoid hemorrhage by digital subtraction angiography"</p> <p>Repository 1: Digital subtraction angiographies of CVS patients for grading with pM1 values</p> <p>Repository 2: Vessel values</p> <p>Repository 3: Clinical data of CVS patients</p>
Extracted data for meta-analysis: Distal versus proximal radial access in coronary angiography
<p>Data base underlying quantitative meta-analysis in the manuscript titled "Distal versus proximal radial access in coronary angiography: A meta-analysis" by Lueg, Schulze, Stöhr, & Leistner.</p> <p>Data allows meta-analysis of primary endpoint (RAO), secondary endpoints, meta-regression for moderator analysis, and publication bias analysis.</p>
OCTAVA: an open-source toolbox for quantitative analysis of optical coherence tomography angiography images
<p>This is a dataset of OCTA images used in the development of the manuscript <em>OCTAVA: an open-source toolbox for quantitative analysis of optical coherence tomography angiography images</em></p>
Determination of Fractional Flow Reserve by Anatomic Computed Tomographic Angiography
ClinicalTrials.gov study NCT01233518. IPD Sharing: NO. Countries: 1. Publications: 3.
CT COMPARE: CT Coronary Angiography to Measure Plaque Reduction
ClinicalTrials.gov study NCT02740699. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Determination of the Effect of Raised Supine Position and Back Support on Back Pain, Anxiety and Comfort Level in Coronary Angiography Patients
ClinicalTrials.gov study NCT05546216. IPD Sharing: NO. Countries: 1. Publications: 1.
Ultra-high-resolution CT vs. Conventional Angiography for Detecting Coronary Heart Disease
ClinicalTrials.gov study NCT04272060. IPD Sharing: NO. Countries: 1. Publications: 7.
Does Routine Pressure Wire Assessment Influence Management Strategy at Coronary Angiography for Diagnosis of Chest Pain?
ClinicalTrials.gov study NCT01070771. IPD Sharing: Not stated. Countries: 2. Publications: 3.
The IAI-OCTA Study; a Study of OCT-Angiography Analysis Efficacy
ClinicalTrials.gov study NCT03022292. IPD Sharing: NO. Countries: 1. Publications: 11.
European Ambulance Acute Coronary Syndrome (ACS) Angiography Trial
ClinicalTrials.gov study NCT01087723. IPD Sharing: Not stated. Countries: 9. Publications: 9.
OPTIMIZE PCI: Multicenter Randomized Trial of OCT Compared to IVUS and Angiography to Guide Coronary Stent Implantation
ClinicalTrials.gov study NCT02471586. IPD Sharing: NO. Countries: 8. Publications: 2.
Transulnar Access in Patients With Ipsilateral Radial Artery Occlusion Undergoing Coronary Angiography or Angioplasty
ClinicalTrials.gov study NCT07380399. IPD Sharing: YES. Countries: 1. Publications: 10.
Optical Coherence Tomography Angiography Evaluation of Ocular Changes in Patients With Carotid Artery Stenosis
ClinicalTrials.gov study NCT04326842. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Dose-varied Evaluation of Ablavar-enhanced MR Angiography of the Central Veins of the Chest in Healthy Participants
ClinicalTrials.gov study NCT01431300. IPD Sharing: Not stated. Countries: 1. Publications: 1.
HeartFlowNXT - HeartFlow Analysis of Coronary Blood Flow Using Coronary CT Angiography
ClinicalTrials.gov study NCT01757678. IPD Sharing: Not stated. Countries: 1. Publications: 5.
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International Brain Laboratory public data
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OpenNeuro
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