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130 results for “Electric impedance tomography”
Accuracy and Reliability of Noninvasive Stroke Volume Monitoring via ECG-Gated 3D Electrical Impedance Tomography in Healthy Volunteers
<p>3D EIT dataset of ten healthy human volunteers, as described in the corresponding <a href="http://dx.doi.org/10.1371/journal.pone.0191870">journal publication at PLOS ONE</a> or the first author's <a href="http://dx.doi.org/10.5075/epfl-thesis-8343">PhD thesis at EPFL</a>. Please also read the attached ReadMe file.</p> <p>When using this data please cite the corresponding journal publication:</p> <blockquote> <p>Accuracy and Reliability of Noninvasive Stroke Volume Monitoring via ECG-Gated 3D Electrical Impedance Tomography in Healthy Volunteers, PLOS ONE, 2018, <a href="http://dx.doi.org/10.1371/journal.pone.0191870">https://dx.doi.org/10.1371/journal.pone.0191870</a></p> </blockquote>
Data and results for manuscript "Multi-frequency electrical impedance tomography as a non-invasive tool to characterize and monitor crop root systems "
<p>Root systems are essential in nutrient uptake and translocation, but are difficult to characterize non-invasively with existing methods. We propose electrical impedance tomography (EIT) as a new tool for the imaging and monitoring of crop root systems. In a laboratory experiment we demonstrate the capability of the method to capture physiological responses of root systems with high spatial and temporal resolution. We conclude that EIT is a promising functional imaging technique for crop roots.</p> <p>This package contains measured raw EIT data, electrical imaging results, spectral results from the Debye decomposition, and the Python scripts used to generate the plots in the manuscript.</p>
2D electrical impedance tomography dataset
<p>This is an open access electrical impedance tomography (EIT) dataset. The EIT measurements were collected from a circular body (a flat tank filled with saline) with various choices of conductive and resistive inclusions.</p> <p>The dataset consists of</p> <ul> <li>current patterns and voltage measurements of a circular tank containing different targets (archive file data_mat_files.zip containing 38 MATLAB Data files),</li> <li>photos of the tank and targets (archive file target_photos.zip containing 38 JPEG files), and</li> <li>MATLAB code for reading the data (MATLAB code file LoadData.m).</li> </ul> <p>Documentation of the dataset is available at <a href="https://arxiv.org/abs/1704.01178">arxiv.org/abs/1704.01178</a>. See also <a href="https://www.fips.fi/EIT_dataset.php">www.fips.fi/EIT_dataset.php</a>.</p> <p>The data was collected at the University of Eastern Finland.</p>
Experimental Electrical Impedance Tomography Data Set Using the Spectra Bioimpedance and EIT Complete Kit
<p><strong>Abstract</strong></p> <p>The amount of open-source EIT measurement data is low. This data set concerns the acquisition and processing of different measurement data using the SpectraEIT-Kit as well as information about the deposited files.</p> <p><strong>Aknoelegenment</strong><br> Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – SFB 1270/2 - 299150580.</p>
Electrical impedance tomography - Depency of cardiac related impedance change amplitudes on body position and reconstruction algorithm
<p>Dataset of a publication investigating the influence of body position and reconstruction algorithm on the amplitudes of cardiac related impedance changes in healthy adult volunteers.</p>
Kuopio Tomography Challenge 2023 open electrical impedance tomographic dataset (KTC 2023)
<p><strong>Notice: v3 update 17.4.2023. Ground truth images were corrected slightly. The older ground truth images had a geometric distortion caused by cropping the photographs to the outer boundary of the imaging chamber, instead of the inner boundary on which the measurement electrodes were located. In addition, version 3 now contains both the limited EIT data used in the challenge evaluation, as well as the full EIT data with no measurements left out.</strong></p> <p><strong>It is recommended to download version v3 and replace the v2 version with it if using the data for research purposes.</strong></p> <p>This dataset is primarily designed for the Kuopio Tomography Challenge 2023 (KTC 2023), but it can be used for generic algorithm research and development in 2D Electric Impedance Tomography (EIT) image reconstruction. The purpose of KTC 2023 is to develop algorithms for electric impedance tomography image reconstruction with limited data.</p> <p>The dataset contains electric impedance tomography data collected from phantoms made up of a cylindrical water chamber with inclusions of varying shapes and sizes present. The data consists of electrical measurements collected using electrodes placed at the chamber boundary, i.e. the values of electric current injected between two electrodes at a time, and the resulting voltages between adjacent electrode pairs. The data has been stored in the MATLAB .mat format.</p> <p>The training dataset contains data measured from five training phantoms. These are designed to facilitate algorithm development and benchmarking for the challenge itself. Four of the training phantoms contained inclusions, which were either resistive or conductive in comparison to the water in the imaging chamber. The fifth training phantom was the imaging chamber filled with only water. We encourage subsampling these datasets to create limited datasets and comparing the reconstruction results to the ground truth obtainable from the full electrode data.</p> <p>The actual challenge data is arranged into seven different difficulty levels, labeled 1-7, with each level containing three different phantoms, labeled A-C. As the difficulty level increases, the number of inclusions increases and their shapes become increasingly complex. Furthermore, the measurement data is made more limited by removing measurements collected by some of the electrodes. At each difficulty level above level 1, the data collected from two of the boundary electrodes is removed.</p> <p>To illustrate a solution to the KTC2023, we have included a simple example reconstruction algorithm, and a Finite Element Method based forward solver used by the reconstruction algorithm. These are provided as both Matlab and Python codes. The reconstructions were computed using linearized difference imaging, and the resulting (EIT) images were then segmented using Otsu's method.</p> <p>The competitors do not need to follow the above procedure, and are encouraged to explore various image reconstruction and segmentation techniques.</p> <p>The full data for all the test phantoms will be released after the Kuopio Tomography Challenge 2023 has ended. This data has now been added to this dataset as EvaluationData.zip.</p> <p>All measurements were conducted at the Process Tomography Laboratory at the University of Eastern Finland.</p> <p> </p> <p> </p>
Dataset from the Study: "A non-invasive approach to skin cancer diagnosis via graphene electrical tattoos and electrical impedance tomography"
<p>This repository contains the scripts and other resources used in:</p> <p>“A non-invasive approach to skin cancer diagnosis via graphene electrical tattoos and electrical impedance tomography”, Lee H et al. 10.1088/1361-6579/ad3d26</p> <p> </p> <p>>> THIS DATA IS FREE FOR USE IN ANY SCIENTIFIC RESEARCH WITH CITATION (PLEASE USE THE DOI FOR PRECISE CITATION): DOI 10.1088/1361-6579/ad3d26</p> <p> </p> <p>>> IF YOU USE THESE RESOURCES, CITE!!!</p> <p> </p> <p>The repository contains the phantom experimental data and the code and resources to generate the numerical/computational models.</p> <p> </p> <p>Note:</p> <p>Software used in this study:</p> <ul> <li>MATLAB</li> <li>EIDORS </li> </ul> <p>Measurement system used in this study:</p> <ul> <li>Sciospec EIT32 system</li> </ul>
Electrical Impedance Tomography (EIT) measurement monitoring the respiratory status
<p>This dataset was used in a study titled "Structural priors represented by discrete cosine transform improve EIT functional imaging" which is currently pending publication. The dataset consists of Electrical Impedance Tomography (EIT) measurements that were collected during the monitoring of respiratory status in tested subjects. The data is stored as .get files, which can be imported into the Matlab® workspace using the codes provided on GitHub at https://github.com/rongqing-chen/DCT-EIT.</p> <p>Using the dataset requires the citation of the following publication:</p> <ul> <li>Lovas A, Chen R, Molnár T, Benyó B, Szlávecz Á, Hawchar F, et al. Differentiating Phenotypes of Coronavirus Disease-2019 Pneumonia by Electric Impedance Tomography. Frontiers in Medicine. 2022;9. doi: 10.3389/fmed.2022.747570</li> <li>R. Chen, S. Krueger-Ziolek, A. Lovas, B. Benyó, S.J. Rupitsch, K. Moeller (2023) Structural priors represented by discrete cosine transform improve EIT functional imaging. PLoS ONE 18(5): e0285619. 10.1371/journal.pone.0285619</li> </ul>
An Extensive Dataset of Geometric Objects Placed in a Watertank for Electrical Impedance Tomography
<p>Open-access experimental Electrical Impedance Tomography (EIT) data set.<br> The measurements were generated using the ScioSpec EIT device from which 16 electrodes were connected to a phantom tank filled with saline. Four 3D-printed cylindrical objects of different sizes were placed in this tank area-wide. Adjacent and opposite injection patterns have been used to measure large datasets with more than 125000 samples.</p> <p>The tutorial can be found here: https://github.com/JacobTh98/sciospeceit/blob/main/tutorial.ipynb</p> <p>Contact: jacob.thoenes@uni-rostock.de</p>
Electrical Impedance Tomography for Optimization of Positive End-Expiratory Pressure: Acute Respiratory Distress Syndrome
ClinicalTrials.gov study NCT03793842. IPD Sharing: NO. Countries: 1. Publications: 1.
Effects of individualized Electrical Impedance Tomography and image reconstruction settings upon the assessment of regional ventilation distribution: Comparison to 4-dimensional Computed Tomography in a porcine model
<p>Reconstruction Models used for identification of optimal settings for comparison to CT images. Forward models are available in the supplement of the article but were removed form the inverse models due to redundance storage within each model.</p> <p>Prior reconstruction in EIDORS, forward models have to be added again to<em> imdl.fwd_model</em> and <em>imdl.jacobian_background.fwd_model</em>.</p>
Open Extensive 3D Dataset of Geometric Objects Placed in a Watertank for Electrical Impedance Tomography
<p>Electrical impedance tomography (EIT) is a non-invasive, radiation-free imaging method for visualizing the tomography of electrically conductive objects. The image reconstruction approach using data-driven methods or deep neural networks (DNN) has become very popular. To train such a reconstruction network, much data is required to reconstruct the conductivity distribution reliably, which is why simulation data are often used. This is an open-access experimental 3D EIT data set. The measurements were generated using the Sciospec EIT device, from which 64 electrodes were connected in two stages, with 32 electrodes, to a phantom tank filled with saline. Various ball objects of different sizes and materials were placed in this tank volume-wide. The provided dataset contains more than 124,000 samples.</p>
Dataset from the study: "Brain Haemorrhage Detection using a SVM Classifier with Electrical Impedance Tomography Measurement Frames"
<p>This repository contains the scripts and other resources used in:</p> <p>“Brain Haemorrhage Detection using a SVM Classifier with Electrical Impedance Tomography Measurement Frames”, McDermott B et al. 10.1371/journal.pone.0200469</p> <p> </p> <p>>> THIS DATA IS FREE FOR USE IN ANY SCIENTIFIC RESEARCH WITH CITATION (PLEASE USE THE DOI FOR PRECISE CITATION): DOI 10.1371/journal.pone.0200469</p> <p> </p> <p>>> IF YOU USE THESE RESOURCES, CITE!!!</p> <p> </p> <p>The repository contains the code and resources to generate the EIT Measurement Frames used in Numerical Models (STL models, code to mesh, code to generate frames)</p> <p> </p> <p>Also included are the Measurement Frames generated from the Phantom Studies.</p> <p> </p> <p><strong>=> This is all the data (how to replicate it for numerical studies and the actual data for the phantom part) used in the study</strong></p> <p> </p> <p>Classifier generation, training, testing, cross validation etc uses standard MATLAB methods and resources: fitcsvm() etc.</p> <p> </p> <p>The subfolders are ordered numerically in the logical order of use</p> <p>The subfolders contain text files with more details and description relevant to the contents of the respective subfolder.</p> <p> </p> <p>Note:</p> <p> </p> <p>Software used in this study:</p> <p>At a minimum the first 2 will be needed to be installed on your computer</p> <p>(other methods etc needed are detailed within the folders)</p> <p> </p> <p><strong>MATLAB 2017B</strong> (<a href="https://uk.mathworks.com/products/matlab.html">https://uk.mathworks.com/products/matlab.html</a>):</p> <p>The primary software tool used throughout</p> <p> </p> <p><strong>EIDORS </strong>(<a href="http://eidors3d.sourceforge.net/index.shtml">http://eidors3d.sourceforge.net/index.shtml</a>)<strong>: </strong></p> <p>Open Source software package, compatible with MATLAB, with tools for use in Electrical Impedance Tomography studies.</p> <p> </p> <p><strong>Autodesk Fusion 360</strong> (<a href="https://www.autodesk.com/products/fusion-360/overview?mktvar002=685209&mkwid=sMHGuhLcc%7Cpcrid%7C209188650131%7Cpkw%7Cfusion%20360%7Cpmt%7Ce%7Cpdv%7Cc%7Cslid%7C%7Cpgrid%7C34851227038%7Cptaid%7Ckwd-11029869505%7C&intent=&utm_medium=cpc&utm_source=google&utm_campaign=GGL_Fusion+360_IE_BR_SEM&utm_term=fusion%20360&utm_content=sMHGuhLcc%7Cpcrid%7C209188650131%7Cpkw%7Cfusion%20360%7Cpmt%7Ce%7Cpdv%7Cc%7Cslid%7C%7Cpgrid%7C34851227038%7Cptaid%7Ckwd-11029869505%7C&gclid=Cj0KCQjw1NzZBRCoARIsAIaMwut5zqUE_d7oieOvw6H3SpU45Jw7vwL5KAKqyRYW20Be6QWE-V3HaB0aAnW0EALw_wcB">https://www.autodesk.com/products/fusion-360/overview?mktvar002=685209&mkwid=sMHGuhLcc|pcrid|209188650131|pkw|fusion%20360|pmt|e|pdv|c|slid||pgrid|34851227038|ptaid|kwd-11029869505|&intent=&utm_medium=cpc&utm_source=google&utm_campaign=GGL_Fusion+360_IE_BR_SEM&utm_term=fusion%20360&utm_content=sMHGuhLcc|pcrid|209188650131|pkw|fusion%20360|pmt|e|pdv|c|slid||pgrid|34851227038|ptaid|kwd-11029869505|&gclid=Cj0KCQjw1NzZBRCoARIsAIaMwut5zqUE_d7oieOvw6H3SpU45Jw7vwL5KAKqyRYW20Be6QWE-V3HaB0aAnW0EALw_wcB</a>):</p> <p>Used to generate the head, brain and lesion STL files. These final STL files are provided in this repository.</p>
Neonate head mesh for Electrical Impedance Tomography - coarse
<p>A head mesh for EIT made by https://github.com/EIT-team/Mesher for https://github.com/EIT-team/PEITS.</p> <p>This archive is used for Travis CI</p>
Electrical Impedance Tomography in One-Lung Ventilation
ClinicalTrials.gov study NCT03728010. IPD Sharing: NO. Countries: 1. Publications: 5.
Pressure Opening With Electrical Impedance Tomography
ClinicalTrials.gov study NCT05825534. IPD Sharing: NO. Countries: 1. Publications: 1.
Ventilatory Strategies After Cardiopulmonary Bypass Evaluated by Electrical Impedance Tomography
ClinicalTrials.gov study NCT04813250. IPD Sharing: YES. Countries: 1. Publications: 1.
Gastroplasty and Electrical Impedance Tomography
ClinicalTrials.gov study NCT03476863. IPD Sharing: NO. Countries: 1. Publications: 2.
Non-invasive Estimation of Pulmonary Artery Pressure in Healthy Subjects by Electrical Impedance Tomography
ClinicalTrials.gov study NCT02969486. IPD Sharing: NO. Countries: 1. Publications: 4.
Clinical Application of Electrical Impedance Tomography for Individual Adjustment of Ventilator Settings
ClinicalTrials.gov study NCT02703012. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
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