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  2. In silico electrocardiograms of 1.8 million ventricular extrasystoles and corresponding activation maps (part 3)
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    Datenpaket: In silico electrocardiograms of 1.8 million ventricular extrasystoles and corresponding activation maps (part 3)

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    Alternativer Identifier:
    (KITopen-DOI) 10.5445/IR/1000156555
    Verwandter Identifier:
    -
    Ersteller/in:
    Pilia, Nicolas [Institut für Biomedizinische Technik]

    Schuler, Steffen [Institut für Biomedizinische Technik]

    Rees, Maike [Institut für Biomedizinische Technik]

    Moik, Gerald [Institut für Biomedizinische Technik]

    Potyagaylo, Danila [Institut für Biomedizinische Technik]

    Dössel, Olaf [Institut für Biomedizinische Technik]

    Loewe, Axel https://orcid.org/This dataset contains about 1.8 million body surface potentials (BSPs) simulated using 1000 heart models generated using a statistical shape model. It has been used in [1,1a]. Here, only the noise-free BSPs are provided. Due to its size, this is a multi-part dataset. Part 1: https://doi.org/10.5445/IR/1000156139 Part 2: https://doi.org/10.5445/IR/1000156554 Part 3: https://doi.org/10.5445/IR/1000156555 Part 4: https://doi.org/10.5445/IR/1000156556 Part 5: https://doi.org/10.5445/IR/1000156557 Each archive XXXX-YYYY.tar contains 20 heart models and corresponding signals. Each subdirectory within the archive contains: - heart.vtp: A triangle mesh of the heart including the point data: - ab, rt, rtCos, rtSin, tm, tv: Consistent biventricular coordinates [2]. - class: Boundary regions used as input for the computation of fiber orientations [3]. - trigger: 1-based indices of the ca. 600 foci (-1000 if not a focus). - heart_transform_matrices.mat: A 1 x 3 cell array containing 4 x 4 transformation matrices that describe the pose of the heart within the torso. Apply the matrix from heart_transform_matrices.mat to the nodes in heart.vtp. - actTimes.mat: A numNodes x numFoci matrix of activation times computed using the fast iterative method [4,5] (conduction velocity in fiber direction: 1 m/s, perpendicular to fiber direction: 1/2.7 m/s). - bsp.mat: - bsp: A numElectrodes x numTimeSamples x numHeartPoses x numFoci matrix of BSPs computed by aligning a transmembrane voltage template with scaled activation times (see actTimeScalings.mat below) and solving the second bidomain equation using the boundary element method [6]. - bspEnd: Time index of the end of depolarization (largest scaled activation time). The archive general.tar contains heart-model-independent data and parameters used to generate the individual heart models: - torso.vtp: A triangle mesh of the torso including the point data: - electrodes: 1-based indices of the 200 electrodes (-1000 if not an electrode). - heart_meanshape.vtp: A triangle mesh of the mean shape of the statistical shape model [7,8]. - heart_shapemodel.mat: - pc: A 3*numNodes x numModes matrix of principal components (numModes = 100). - var: A numModes x 1 vector of variances. - weights: A numModes x numModels matrix of weights used to generate the 1000 heart models. - heart_alignment_matrix.mat: A 4 x 4 transformation matrix describing the alignment of the mean shape with the torso-specific heart. Only to be appleid to node coordinates in within general.tar (already contained in heart_transform_matrices.mat). - heart_transform_params.mat: A struct containing roll, pitch, yaw angles and x, y, z translations used to generate the heart_transform_matrices.mat (see above). - fiber_angles.mat: - alphaEndo: numModels x 1 vector of endocardial fiber angles used to generate fiber orientations. - alphaEpi: numModels x 1 vector of epicardial fiber angles used to generate fiber orientations. - actTimeScalings.mat: - A numModels x numFoci matrix of factors used to scale the activation times. - tmv_template.mat: The transmembrane voltage time course used to compute BSPs. - heart_classes.vtp: A coarse triangle mesh of the mean shape used for fuzzy classification. - heart_classes_subdiv.vtp: A subdivided version of the coarse triangle mesh of the mean shape used to convert between Cobiveco and barycentric coordinates. [1] https://doi.org/10.48550/arXiv.2209.08095 [1a]https://doi.org/10.1016/j.artmed.2023.102619 [2] https://doi.org/10.1016/j.media.2021.102247 [3] https://github.com/KIT-IBT/LDRB_Fibers [4] https://github.com/KIT-IBT/FIM_Eikonal [5] https://doi.org/10.1137/120881956 [6] https://doi.org/10.1016/j.cmpb.2007.09.004 [7] https://doi.org/10.5281/zenodo.4506463 [8] https://doi.org/10.1016/j.media.2015.08.009 [Institut für Biomedizinische Technik]
    Beitragende:
    -
    Titel:
    In silico electrocardiograms of 1.8 million ventricular extrasystoles and corresponding activation maps (part 3)
    Weitere Titel:
    -
    Beschreibung:
    (Abstract) 1.8 million ECGs derived from multiscale simulations of cardiac electrophysiology of ventricular extrasystoles. 1000 anatomical variants of a bi-ventricular mesh x 600 excitation origins x 3 heart posiitions in the torso.

    1.8 million ECGs derived from multiscale simulations of cardiac electrophysiology of ventricular extrasystoles. 1000 anatomical variants of a bi-ventricular mesh x 600 excitation origins x 3 heart posiitions in the torso.


    (Technical Remarks) This dataset contains about 1.8 million body surface potentials (BSPs) simulated using 1000 heart models generated using a statistical shape model. It has been used in [1,1a]. Here, only the noise-free BSPs are provided. Due to its size, this is a multi-part dataset. Part 1: https://doi.org/10.5445/... This dataset contains about 1.8 million body surface potentials (BSPs) simulated using 1000 heart models generated using a statistical shape model. It has been used in [1,1a]. Here, only the noise-free BSPs are provided. Due to its size, this is a multi-part dataset. Part 1: https://doi.org/10.5445/IR/1000156139 Part 2: https://doi.org/10.5445/IR/1000156554 Part 3: https://doi.org/10.5445/IR/1000156555 Part 4: https://doi.org/10.5445/IR/1000156556 Part 5: https://doi.org/10.5445/IR/1000156557 Each archive XXXX-YYYY.tar contains 20 heart models and corresponding signals. Each subdirectory within the archive contains: - heart.vtp: A triangle mesh of the heart including the point data: - ab, rt, rtCos, rtSin, tm, tv: Consistent biventricular coordinates [2]. - class: Boundary regions used as input for the computation of fiber orientations [3]. - trigger: 1-based indices of the ca. 600 foci (-1000 if not a focus). - heart_transform_matrices.mat: A 1 x 3 cell array containing 4 x 4 transformation matrices that describe the pose of the heart within the torso. Apply the matrix from heart_transform_matrices.mat to the nodes in heart.vtp. - actTimes.mat: A numNodes x numFoci matrix of activation times computed using the fast iterative method [4,5] (conduction velocity in fiber direction: 1 m/s, perpendicular to fiber direction: 1/2.7 m/s). - bsp.mat: - bsp: A numElectrodes x numTimeSamples x numHeartPoses x numFoci matrix of BSPs computed by aligning a transmembrane voltage template with scaled activation times (see actTimeScalings.mat below) and solving the second bidomain equation using the boundary element method [6]. - bspEnd: Time index of the end of depolarization (largest scaled activation time). The archive general.tar contains heart-model-independent data and parameters used to generate the individual heart models: - torso.vtp: A triangle mesh of the torso including the point data: - electrodes: 1-based indices of the 200 electrodes (-1000 if not an electrode). - heart_meanshape.vtp: A triangle mesh of the mean shape of the statistical shape model [7,8]. - heart_shapemodel.mat: - pc: A 3*numNodes x numModes matrix of principal components (numModes = 100). - var: A numModes x 1 vector of variances. - weights: A numModes x numModels matrix of weights used to generate the 1000 heart models. - heart_alignment_matrix.mat: A 4 x 4 transformation matrix describing the alignment of the mean shape with the torso-specific heart. Only to be appleid to node coordinates in within general.tar (already contained in heart_transform_matrices.mat). - heart_transform_params.mat: A struct containing roll, pitch, yaw angles and x, y, z translations used to generate the heart_transform_matrices.mat (see above). - fiber_angles.mat: - alphaEndo: numModels x 1 vector of endocardial fiber angles used to generate fiber orientations. - alphaEpi: numModels x 1 vector of epicardial fiber angles used to generate fiber orientations. - actTimeScalings.mat: - A numModels x numFoci matrix of factors used to scale the activation times. - tmv_template.mat: The transmembrane voltage time course used to compute BSPs. - heart_classes.vtp: A coarse triangle mesh of the mean shape used for fuzzy classification. - heart_classes_subdiv.vtp: A subdivided version of the coarse triangle mesh of the mean shape used to convert between Cobiveco and barycentric coordinates. [1] https://doi.org/10.48550/arXiv.2209.08095 [1a]https://doi.org/10.1016/j.artmed.2023.102619 [2] https://doi.org/10.1016/j.media.2021.102247 [3] https://github.com/KIT-IBT/LDRB_Fibers [4] https://github.com/KIT-IBT/FIM_Eikonal [5] https://doi.org/10.1137/120881956 [6] https://doi.org/10.1016/j.cmpb.2007.09.004 [7] https://doi.org/10.5281/zenodo.4506463 [8] https://doi.org/10.1016/j.media.2015.08.009

    This dataset contains about 1.8 million body surface potentials (BSPs) simulated using 1000 heart models generated using a statistical shape model. It has been used in [1,1a]. Here, only the noise-free BSPs are provided. Due to its size, this is a multi-part dataset. Part 1: https://doi.org/10.5445/IR/1000156139 Part 2: https://doi.org/10.5445/IR/1000156554 Part 3: https://doi.org/10.5445/IR/1000156555 Part 4: https://doi.org/10.5445/IR/1000156556 Part 5: https://doi.org/10.5445/IR/1000156557 Each archive XXXX-YYYY.tar contains 20 heart models and corresponding signals. Each subdirectory within the archive contains:

    • heart.vtp: A triangle mesh of the heart including the point data:
      • ab, rt, rtCos, rtSin, tm, tv: Consistent biventricular coordinates [2].
      • class: Boundary regions used as input for the computation of fiber orientations [3].
      • trigger: 1-based indices of the ca. 600 foci (-1000 if not a focus).
    • heart_transform_matrices.mat: A 1 x 3 cell array containing 4 x 4 transformation matrices that describe the pose of the heart within the torso. Apply the matrix from heart_transform_matrices.mat to the nodes in heart.vtp.
    • actTimes.mat: A numNodes x numFoci matrix of activation times computed using the fast iterative method [4,5] (conduction velocity in fiber direction: 1 m/s, perpendicular to fiber direction: 1/2.7 m/s).
    • bsp.mat:
      • bsp: A numElectrodes x numTimeSamples x numHeartPoses x numFoci matrix of BSPs computed by aligning a transmembrane voltage template with scaled activation times (see actTimeScalings.mat below) and solving the second bidomain equation using the boundary element method [6].
      • bspEnd: Time index of the end of depolarization (largest scaled activation time). The archive general.tar contains heart-model-independent data and parameters used to generate the individual heart models:
    • torso.vtp: A triangle mesh of the torso including the point data:
      • electrodes: 1-based indices of the 200 electrodes (-1000 if not an electrode).
    • heart_meanshape.vtp: A triangle mesh of the mean shape of the statistical shape model [7,8].
    • heart_shapemodel.mat:
      • pc: A 3*numNodes x numModes matrix of principal components (numModes = 100).
      • var: A numModes x 1 vector of variances.
      • weights: A numModes x numModels matrix of weights used to generate the 1000 heart models.
    • heart_alignment_matrix.mat: A 4 x 4 transformation matrix describing the alignment of the mean shape with the torso-specific heart. Only to be appleid to node coordinates in within general.tar (already contained in heart_transform_matrices.mat).
    • heart_transform_params.mat: A struct containing roll, pitch, yaw angles and x, y, z translations used to generate the heart_transform_matrices.mat (see above).
    • fiber_angles.mat:
      • alphaEndo: numModels x 1 vector of endocardial fiber angles used to generate fiber orientations.
      • alphaEpi: numModels x 1 vector of epicardial fiber angles used to generate fiber orientations.
    • actTimeScalings.mat:
      • A numModels x numFoci matrix of factors used to scale the activation times.
    • tmv_template.mat: The transmembrane voltage time course used to compute BSPs.
    • heart_classes.vtp: A coarse triangle mesh of the mean shape used for fuzzy classification.
    • heart_classes_subdiv.vtp: A subdivided version of the coarse triangle mesh of the mean shape used to convert between Cobiveco and barycentric coordinates. [1] https://doi.org/10.48550/arXiv.2209.08095 [1a]https://doi.org/10.1016/j.artmed.2023.102619 [2] https://doi.org/10.1016/j.media.2021.102247 [3] https://github.com/KIT-IBT/LDRB_Fibers [4] https://github.com/KIT-IBT/FIM_Eikonal [5] https://doi.org/10.1137/120881956 [6] https://doi.org/10.1016/j.cmpb.2007.09.004 [7] https://doi.org/10.5281/zenodo.4506463 [8] https://doi.org/10.1016/j.media.2015.08.009
    Zeige alles Zeige Markdown
    Schlagworte:
    ECG
    in silico
    extrasystoles
    Zugehörige Informationen:
    -
    Sprache:
    -
    Herausgeber/in:
    Karlsruhe Institute of Technology
    Erstellungsjahr:
    2023
    Fachgebiet:
    Engineering
    Objekttyp:
    Dataset
    Datenquelle:
    -
    Verwendete Software:
    -
    Datenverarbeitung:
    -
    Erscheinungsjahr:
    2023
    Rechteinhaber/in:
    Pilia, Nicolas

    Schuler, Steffen

    Rees, Maike

    Moik, Gerald

    Potyagaylo, Danila

    Dössel, Olaf

    Loewe, Axel https://orcid.org/0000-0002-2487-4744
    Förderung:
    -
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    Name Speichervolumen Metadaten Upload Aktion
    Status:
    Publiziert
    Eingestellt von:
    kitopen
    Erstellt am:
    2023-04-20
    Archivierungsdatum:
    2023-06-24
    Archivgröße:
    189,6 GB
    Archiversteller:
    kitopen
    Archiv-Prüfsumme:
    abf60816d9f40766b117e57326bda910 (MD5)
    Embargo-Zeitraum:
    -
    Die Metadaten wurden nachträglich korrigiert. Die ursprünglichen Metadaten sind nach Download des Datenpakets verfügbar.
    dataset/In silico electrocardiograms of 1.8 million ventricular extrasystoles and corresponding activation maps (part 3)
    DOI: 10.35097/1534
    Publikationsdatum: 2023-06-24
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    Pilia, Nicolas; Schuler, Steffen; Rees, Maike; et al. (2023): In silico electrocardiograms of 1.8 million ventricular extrasystoles and corresponding activation maps (part 3). Karlsruhe Institute of Technology. DOI: 10.35097/1534
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