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167 results for “electrical impedance”
Simulated Local Electrical Impedance in Atrial Tissue With Varying Contact Force
<p>In this dataset we can find geometrical setups that served as an input to carry forward electrical impedance simulations with EIDORS. <br>A 3D geometrical models of one ablation catheters combining measurements of local impedance (LI) and contact force (CF) commercially available is included. The objective of these in silico experiments laid on understanding how CF and tissue deformation affect LI measurements.<br>To achieve it, using the catheter against the tissue, several grams of force are applying.<br>The dataset consists of the original geometrical models before deformation and a couple of examples of the deformed one.</p> <h2>Data structure</h2> <ul> <li>geos: original geometries of the catheter and the tissue in stl <ul> <li>catheter.stl</li> <li>tissue.stl</li> </ul> </li> <li>geos_deformed: deformed geometries at 5 and 10 grams, respectively. Includes the catheter, the mesh, and the tissue <ul> <li>5 g <ul> <li>catheter.stl</li> <li>tissue_5g.stl</li> <li>mesh_5g.stl</li> </ul> </li> <li>10 g <ul> <li>catheter.stl</li> <li>tissue_10g.stl</li> <li>mesh_10g.stl</li> </ul> </li> </ul> </li> </ul>
In Silico Local Electrical Impedance Measurements in the Atria
<div>This document describes a dataset provided in the context of the manuscript “In Silico Study of Local Electrical Impedance Measurements in the Atria - Towards Understanding and Quantifying Dependencies in Human” [1].</div> <div> </div> <div>Authors: Unger LA, Anton CM, Stritt M, Wakili R, Haas A, Kircher M, Dössel O, Luik A</div> <div> </div> <div>The dataset contains in silico simulation setups and results from forward electrical impedance simulations with EIDORS. Geometrical models include the commercially available ablation catheters IntellaNav MiFi and IntellaNav StPt catheter measuring local impedance (LI). </div> <div>Catheter geometries were embedded in different surrounding conditions of clinical importance. Catheter tissue interaction with and without scar, the insertion of the catheter into a pulmonary vein (PV), the withdrawal into a transeptal sheath, and catheter irrigation were modeled to quantify the respective effect on LI measurements. In vitro and clinical data used for validation purposes are included in the dataset as well.</div> <div> </div> <div>Abbreviations: </div> <div>LI: local impedance, all numbers are given in Ohms</div> <div>MiFi: IntellaNav MiFi catheter</div> <div>PV: pulmonary vein</div> <div>StPt: IntellaNav StPt catheter</div> <div> </div> <div> </div> <div>Simulation results, in vitro measurements and clinically measured traces are provided in the following MATLAB files in the subdirectory „results_LI“:</div> <div> </div> <div>• impConductivities.mat</div> <div>In vitro measurements and simulation results for MiFi and StPt in NaCl solutions of different concentrations as described in section III A of the related publication [1]. The struct "impedance" includes the following fields:</div> <div>⁃ conc: concentration of NaCl solutions from in vitro measurements in weight percentages</div> <div>⁃ cond: conductivities of the NaCl solutions from in vitro measurements in S/m</div> <div>⁃ temp: interpolated temperature curves from in vitro measurements in °C</div> <div>⁃ condSim: different conductivities of the NaCl solutions from in silicon experiments in S/m</div> <div>⁃ LI_MiFi_iV: 41x9 matrix with interpolated in vitro LI measurements with the MiFi catheter in 9 different NaCl solutions and at 41 interpolated temperature values</div> <div>⁃ LI_StPt_iV: 41x9 matrix with interpolated in vitro LI measurements with the StPt catheter in 9 different NaCl solutions and at 41 interpolated temperatures values</div> <div>⁃ LI_MiFi_iV_RT: LI values for different NaCl solutions at room temperature interpolated from in vitro MiFi measurements</div> <div>⁃ LI_MiFi_iV_BT: LI values for different NaCl solutions at body temperature interpolated from in vitro MiFi measurements</div> <div>⁃ LI_StPt_iV_RT: LI values for different NaCl solutions at room temperature interpolated from in vitro StPt measurements</div> <div>⁃ LI_StPt_iV_BT: LI values for different NaCl solutions at body temperature interpolated from in vitro StPt measurements</div> <div>⁃ LI_MiFi_sim: LI extracted from simulations with the MiFi catheter for different NaCl solutions</div> <div>⁃ LI_StPt_sim: LI extracted from simulations with the StPt catheter for different NaCl solutions</div> <div> </div> <div>• impSheath.mat</div> <div>Simulation results and clinical measurements of LI with MiFi and StPt for different overlaps with a transeptal sheath as described in section III B of the related publication [1]. The struct „impSheath“ contains the following fields:</div> <div>⁃ distance: vertical distance between catheter tip and distal edge of the sheath in mm. Negative distances describe an insertion of the catheter into the sheath</div> <div>⁃ LI_MiFi_sim: LI extracted from simulations with the MiFi catheter for different vertical distances between catheter tip and distal edge of the sheath corresponding to the field distance</div> <div>⁃ LI_StPt_sim: LI extracted from simulations with the StPt catheter for different vertical distances between catheter tip and distal edge of the sheath corresponding to the field distance</div> <div>⁃ LI_MiFi_cd: 281x2 matrix containing clinical LI measurements with the MiFi catheter in the second column and corresponding time steps in the first column</div> <div>⁃ LI_StPt_cd: 301x2 matrix containing clinical LI measurements with the StPt catheter in the second column and corresponding time steps in the first column</div> <div> </div> <div>• impTissue.mat</div> <div>Simulation results for MiFi and StPt with variable distance and angle between catheter and tissue as described in section III C of the related publication [1]. The struct „impTissue“ contains the following fields:</div> <div>⁃ distance: 25 different distances between catheter tip and endocardial surface in mm</div> <div>⁃ distanceSel: 5 selected distances between catheter tip and endocardial surface in mm</div> <div>⁃ angle: 13 different angles between catheter and endocardial tissue surface in degrees</div> <div>⁃ LI_MiFi_d_alpha: 5x13 matrix with simulated LI values for the MiFi catheter at 5 selected distances (distanceSel) and 13 angles between catheter and tissue.</div> <div>⁃ LI_MiFi_d_90: 25 simulated LI values for the MiFi catheter for different distances between catheter tip and endocardial surface corresponding to the field “distance” for orthogonal catheter placement</div> <div>⁃ LI_StPt_d_alpha: 5x13 matrix with simulated LI values for the StPt catheter at 5 selected distances (distanceSel) and 13 angles between catheter and tissue.</div> <div>⁃ LI_StPt_d_90: 25 simulated LI values for the StPt catheter different distances between catheter tip and endocardial surface corresponding to the field “distance” for orthogonal catheter placement</div> <div> </div> <div>• impTissueScar.mat</div> <div>Simulation results for MiFi and StPt interacting with tissue in the presence of scar as described in section III C of the related publication [1]. The struct „impTissueScar“ contains the following fields:</div> <div>⁃ distance: vertical distance between catheter tip and endocardial surface for all simulation setups in mm</div> <div>⁃ centerX: horizontal distance between the catheter tip and the center of the line of scar for all simulation setups in mm</div> <div>⁃ LI_MiFi3mm: simulated LI for the MiFi catheter for all combinations of horizontal and vertical distances with a central line of scar of 3mm width</div> <div>⁃ LI_StPt3mm: simulated LI for the StPt catheter for all combinations of horizontal and vertical distances with a central line of scar of 3mm width</div> <div>⁃ LI_MiFi6mm: simulated LI for the MiFi catheter for all combinations of horizontal and vertical distances with a central line of scar of 6mm width</div> <div>⁃ LI_StPt6mm: simulated LI for the StPt catheter for all combinations of horizontal and vertical distances with a central line of scar of 6mm width</div> <div> </div> <div>• impPV.mat</div> <div>Simulation results for MiFi and StPt insertion into a pulmonary vein (PV) as described in section III D of the related publication [1]. The struct „impPV“ includes the following fields:</div> <div>⁃ distance: vertical distance between catheter tip and tissue surface in mm. Negative distances describe an insertion of the catheter into the vein.</div> <div>⁃ radius: inner radius of the PV in mm</div> <div>⁃ thickness: thickness of the PV tissue in mm</div> <div>⁃ LI_MiFi_d_r_th: 31x4x4 matrix containing the LI simulation results for the MiFi catheter for all combinations of 31 distances, 4 radii, and 4 thicknesses.</div> <div>⁃ LI_StPt_d_r_th: 31x4x4 matrix containing the LI simulation results for the StPt catheter for all combinations of 31 distances, 4 radii, and 4 thicknesses.</div> <div> </div> <div>• impFlush.mat</div> <div>Simulation results for MiFi and StPt flush with NaCl at different flow rates as described in section III E of the related publication [1]. The struct „impFlush“ includes the following fields:</div> <div>⁃ radius: radius of the NaCl spheres at the irrigation holes in mm</div> <div>⁃ LI_MiFi_NaCl: LI extracted from simulations with MiFi catheter for NaCl irrigation spheres of different sizes corresponding to the respective radius</div> <div>⁃ LI_StPt_NaCl: LI extracted from simulations with StPt catheter for NaCl irrigation spheres of different sizes corresponding to the respective radius</div> <div> </div> <div>Additionally, exemplary geometrical setups and results are provided as VTK files in the subdirectory „selectedGeometriesAndSimResults“:</div> <div> </div> <div>Each VTK file contains the following data fields:</div> <div>⁃ Ids (point data): integer specifying the Id of the respective vertex</div> <div>⁃ Voltage (point data): electric potential of the respective vertex with respect to a reference potential in mV</div> <div>⁃ Conductivity (cell data): conductivity of the material of the respective cell in S/mm</div> <div>⁃ Current (cell data): current density of the respective cell in nA/mm^2</div> <div>⁃ Ids (cell data): integer specifying the Id of the respective cell</div> <div>⁃ Material (cell data): integer specifying the material of the respective cell (for MiFi setups: 1: distal ring electrode, 2: middle ring electrode, 3: proximal ring electrode, 4: tip electrode, 5: outer insulator, 6: inner insulator, 7: mini electrode 1, 8: insulator mini electrode 1, 9: mini electrode 2, 10: insulator mini electrode 2, 11: mini electrode 3, 12: insulator mini electrode 3, 13: tissue, 14: blood, 15: sheath, 16:NaCl, 17: scar tissue; for StPt setups: 1: distal ring electrode, 2: middle ring electrode, 3: proximal ring electrode, 4: tip electrode, 5: outer insulator, 6: inner insulator, 7: tissue, 8: blood, 9: NaCl, 10: scar tissue)</div> <div> </div> <div>• mifi.vtk: MiFi catheter in blood </div> <div>• stpt.vtk: StPt catheter in blood</div> <div>• mifiTissue_dist000_angle0000.vtk: MiFi catheter positioned in 0mm distance to the endocardial tissue at an angle of 0°</div> <div>• mifiTissue_dist000_angle0450.vtk: MiFi catheter positioned in 0mm distance to the endocardial tissue at an angle of 45°</div> <div>• mifiTissue_dist000_angle0900.vtk: MiFi catheter positioned in 0mm distance to the endocardial tissue at an angle of 90°</div> <div>• mifiTissue_dist000_angle1350.vtk: MiFi catheter positioned in 0mm distance to the endocardial tissue at an angle of 135°</div> <div>• mifiTissue_dist000_angle1800.vtk: MiFi catheter positioned in 0mm distance to the endocardial tissue at an angle of 180°</div> <div>• mifiTissueScar_dist0000_angle0900_centerX0000_line3mm.vtk: MiFi catheter positioned centrally and orthogonally at a line of scar tissue of 3mm width</div> <div>• mifiTissueScar_dist0000_angle0900_centerX0000_line6mm.vtk: MiFi catheter positioned centrally and orthogonally at a line of scar tissue of 6mm width</div> <div>• mifi_PV_d0060_r030_th20.vtk: MiFi catheter 6mm above the endocardial surface with a PV of 3 mm radius and 2mm PV tissue thickness</div> <div>• mifi_PV_d-070_r030_th20.vtk: MiFi catheter inserted into a PV of 3 mm radius and 2mm PV tissue thickness; insertion depth = 7mm</div> <div>• mifi_flush_050-0.50.vtk: MiFi catheter within blood with NaCl spheres of 0.5mm radius at irrigation holes</div> <div>• mifi_sheath_0100.vtk: MiFi catheter within transeptal sheath extracted by 10mm</div> <div> </div> <div>[1] Unger LA, Anton CM, Stritt M, Wakili R, Haas A, Kircher M, Dossel O, Luik A. In Silico Study of Local Electrical Impedance Measurements in the Atria - Towards Understanding and Quantifying Dependencies in Human. IEEE Trans Biomed Eng. 2023 Feb;70(2):533-543. doi: 10.1109/TBME.2022.3196545. Epub 2023 Jan 19. PMID: 35925848.</div> <p> </p>
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>
Impedance data for various electrochemical and electrical systems
<p>Impedance dataset for different electrochemical and electrical systems:</p> <table> <tbody> <tr> <td> </td> <td> <p><strong>Lithium-Ion battery LFP (A123 26650)</strong></p> </td> <td> <p><strong>Lithium-Ion battery NCR (Panasonic 18650)</strong></p> </td> <td><strong>Vanadium redox-flow Battery</strong></td> <td><strong>Polymer electrolyte membrane fuel cell</strong></td> <td> <p><strong>High-temperature PEM (Custom made)</strong></p> </td> <td> <p><strong>Double-layer capacitor 3.4 kF (Maxwell)</strong></p> </td> <td> <p><strong>Analogue RLC circuit (Custom made)</strong></p> </td> </tr> <tr> <td>Details</td> <td>A123 Systems, <br>26650 lithium iron phosphate | graphite, 2,5 Ah</td> <td>Panasonic NCR-18650B, 18650 nickel-manganese-cobalt-oxid | graphite, 2.5 Ah</td> <td>Micro Flow Cell<br> (Electrocell A/S, Tarm, DK), surface 10 cm2 </td> <td>ElringKlinger<br>(EK) single PEM fuel cell, active surface area 50 cm2 </td> <td>Custom made fuel cell assembly, metallic bipolar plates with single serpentine flow-fields, electrode surface area of 4 cm², polybenzimidazole (PBI) membranes (Dapazol1, Danish Power Systems-DPS1) </td> <td>Maxwell, capacitance 3400 F, 2.85 V</td> <td>Custom made circuit with a parallel connection of a 2.2 μF foil capacitor and a lossy inductor with 9.7 mΩ and 5 mH, factory values may vary ± 10 %</td> </tr> <tr> <td>Operating point</td> <td>50% state of charge, 3.27 V, 20 °C</td> <td>50 % state of charge, 3.27 V, 20 °C</td> <td>50% state of charge, 1:4 V </td> <td>1 A, RH of 83.4%, stoichiometry of 4.0/2.0</td> <td>H2 / air stoichiometry 1.8 / 2.5, 160 °C, 800 mA/cm²</td> <td>voltage 603.5 mV, temperature 30 °C</td> <td>-</td> </tr> <tr> <td>Device</td> <td>Zahner Zennium Pro workstation</td> <td>Zahner Zennium Pro workstation</td> <td>Scribner 857, Gamry Reference 3000</td> <td>Scribner Associates fuel cell test station with 885 Fuel Cell Potentiostat</td> <td>Zahner Zennium Pro workstation</td> <td>Zahner Zennium Pro workstation</td> <td>Biologic VMP300</td> </tr> <tr> <td>EIS mode</td> <td>galvanostatic</td> <td>galvanostatic</td> <td>potentiostatic</td> <td>galvanostatic</td> <td>galvanostatic</td> <td>potentiostatic</td> <td>galvanostatic</td> </tr> <tr> <td>Amplitude</td> <td>30 mA</td> <td>250 mA</td> <td>10 mV</td> <td>100 mA</td> <td>100 mA</td> <td>10 mV</td> <td>30 mA</td> </tr> <tr> <td>Frequency</td> <td>52 mHz - 17 kHz</td> <td>10 mHz - 10 kHz</td> <td>100 mHz - 10 kHz</td> <td>10 mHz - 3.98 kHz</td> <td>100 mHz - 100 kHz</td> <td>100 mHz - 1 kHz</td> <td>100 Hz - 10 kHz</td> </tr> <tr> <td>Reference</td> <td>Danzer, M.A. (2019). Generalized Distribution of Relaxation Times Analysis for the Characterization of Impedance Spectra.</td> <td>Rüther, T., Schamel, M., Plank, C., Schomburg, F., Röder, F., & Danzer, M. A. (2023). Cell-to-Cell-Variations of a Panasonic NCR18650B. Zenodo. https://doi.org/10.5281/zenodo.8369275</td> <td> <p>Danzer, M.A. (2019). Generalized Distribution of Relaxation Times Analysis for the Characterization of Impedance Spectra.</p> <p>Schneider, J., Tichter, T., Khadke, P., Zeis, R., and Roth, C. (2020). Deconvolution of electrochemical impedance data for the monitoring of electrode degradation in VRFB. Electrochimica Acta 336, 135510.</p> <p> </p> </td> <td>Ivan Pivac, Ivar J. Halvorsen, Dario Bezmalinovic, Frano Barbir, & Federico Zenith. (2020). Low-frequency EIS intercept as a diagnostic tool for PEM fuel cells degradation. European Fuel Cell Technology & Applications Conference - Piero Lunghi Conference (EFC17), Naples, Italy. Zenodo. https://doi.org/10.5281/zenodo.3631156</td> <td>Weiß, A., Schindler, S., Galbiati, S., Danzer, M.A., and Zeis, R. (2017). Distribution of Relaxation Times Analysis of High-Temperature PEM Fuel Cell Impedance Spectra. Electrochimica Acta 230, 391–398.</td> <td>Danzer, M.A. (2019). Generalized Distribution of Relaxation Times Analysis for the Characterization of Impedance Spectra.</td> <td>-</td> </tr> </tbody> </table> <p> </p>
Impedance analysis with ELSA and DRT for various electrochemical and electrical systems
<p>Dataset of the analysis of various electrochemical and electrical systems with Electrochemical System Analysis (ELSA) and Distribution of Relaxation Times method (DRT). For full explanation see publication: [[ Electrochemical System Analysis – from impedance data to system identification ]]</p> <p>The impedance dataset used is available at Zenodo for download: doi:10.5281/zenodo.10794584. A detailed information about the systems and the properties of the spectrum can be found there. The following systems were analyzed:</p> <table> <tbody> <tr> <td> </td> <td> <p><strong>Lithium-Ion battery LFP (A123 26650)</strong></p> </td> <td> <p><strong>Lithium-Ion battery NCR (Panasonic 18650)</strong></p> </td> <td><strong>Vanadium redox-flow Battery</strong></td> <td><strong>Polymer electrolyte membrane fuel cell</strong></td> <td> <p><strong>High-temperature PEM (Custom made)</strong></p> </td> <td> <p><strong>Double-layer capacitor 3.4 kF (Maxwell)</strong></p> </td> <td> <p><strong>Analogue RLC circuit (Custom made)</strong></p> </td> </tr> <tr> <td>Details</td> <td>A123 Systems, <br>26650 lithium iron phosphate | graphite, 2,5 Ah</td> <td>Panasonic NCR-18650B, 18650 nickel-manganese-cobalt-oxid | graphite, 2.5 Ah</td> <td>Micro Flow Cell<br> (Electrocell A/S, Tarm, DK), surface 10 cm2 </td> <td>ElringKlinger<br>(EK) single PEM fuel cell, active surface area 50 cm2 </td> <td>Custom made fuel cell assembly, metallic bipolar plates with single serpentine flow-fields, electrode surface area of 4 cm², polybenzimidazole (PBI) membranes (Dapazol1, Danish Power Systems-DPS1) </td> <td>Maxwell, capacitance 3400 F, 2.85 V</td> <td>Custom made circuit with a parallel connection of a 2.2 μF foil capacitor and a lossy inductor with 9.7 mΩ and 5 mH, factory values may vary ± 10 %</td> </tr> </tbody> </table> <p>The data is available as .json and as .mat to allow easy import in different programming languages. Please note, that complex data in the .json files are converted to strings and thus need to be converted after importing.</p> <p><strong>Naming convention:</strong></p> <p>[[name of system]]_[[rxx (xx = model order for special cases)]]_[[method]]</p> <p>method: drt, elsa, elsa_simulation (simulated impedance data)</p> <p><strong>Data structure:</strong></p> <p>_meta: metadata for software package used<br>_class: classname for class used<br>config: configuration for the analysis<br>data: input data used for the analysis<br><br>Specific to ELSA:<br>- system: Here, all calculated systems (including zeros, poles, gain, partial fraction decomposition, ...) for every step are saved<br>- impedance: Simulated impedance and residuals for all systems<br><br>Specific to DRT:<br>- drt: Result of DRT calcualtion (including h, h_rc, h_rl, r_0, l_0, c_0, lambda, l_curve, ...)<br>- optimization: Matrices of the linear optimization problem<br>- simulation: Simulated impedance and residuals for calculated DRT<br><br></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>
Data and results for manuscript: "Imaging and functional characterization of crop root systems using spectroscopic electrical impedance measurements"
<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 titled:<br> <br> Imaging and functional characterization of crop root systems using spectroscopic electrical impedance measurement</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.
Electrical Impedance Myography as an Outcome Measure in Amyotrophic Lateral Sclerosis Clinical Trials
ClinicalTrials.gov study NCT00620698. IPD Sharing: Not stated. 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>
ScienceDex guides
Understand access before you commit
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.