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A reference dataset for verifying numerical electrophysiological heart models.

Koch H, Bousseljot RD, Kosch O, Jahnke C, Paetsch I, Fleck E, Schnackenburg B - Biomed Eng Online (2011)

Bottom Line: The latter were recorded simultaneously from the same individuals a few hours after the MRI sessions.A training dataset is made publicly available; datasets for blind testing will remain undisclosed.While the MRI data may provide a common input that can be applied to different numerical heart models, the verification and comparison of different models can be performed by comparing the measured biosignals with forward calculated signals from the models.

View Article: PubMed Central - HTML - PubMed

Affiliation: Physikalisch-Technische Bundesanstalt, Abbestr, 2-12, 10587 Berlin, Germany. hans.koch@ptb.de

ABSTRACT

Background: The evaluation, verification and comparison of different numerical heart models are difficult without a commonly available database that could be utilized as a reference. Our aim was to compile an exemplary dataset.

Methods: The following methods were employed: Magnetic Resonance Imaging (MRI) of heart and torso, Body Surface Potential Maps (BSPM) and MagnetoCardioGraphy (MCG) maps. The latter were recorded simultaneously from the same individuals a few hours after the MRI sessions.

Results: A training dataset is made publicly available; datasets for blind testing will remain undisclosed.

Conclusions: While the MRI data may provide a common input that can be applied to different numerical heart models, the verification and comparison of different models can be performed by comparing the measured biosignals with forward calculated signals from the models.

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Detector configuration of the biomagnetic multichannel system. SQUID configuration consisting of 19 modules; one of the modules schematically shown on right.
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Figure 4: Detector configuration of the biomagnetic multichannel system. SQUID configuration consisting of 19 modules; one of the modules schematically shown on right.

Mentions: The MCG signals were recorded truly synchronously with the BSP signals, with a 304 channel SQUID vector magnetometer system in the Berlin Magnetically Shielded Room II. The SQUID system consists of 19 modules, each containing 16 SQUIDs. Of these, 6 are sensitive to the z component of the magnetic field produced by the heart currents and the other 10 to the perpendicular components. Figure 4 illustrates the configuration.


A reference dataset for verifying numerical electrophysiological heart models.

Koch H, Bousseljot RD, Kosch O, Jahnke C, Paetsch I, Fleck E, Schnackenburg B - Biomed Eng Online (2011)

Detector configuration of the biomagnetic multichannel system. SQUID configuration consisting of 19 modules; one of the modules schematically shown on right.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3037925&req=5

Figure 4: Detector configuration of the biomagnetic multichannel system. SQUID configuration consisting of 19 modules; one of the modules schematically shown on right.
Mentions: The MCG signals were recorded truly synchronously with the BSP signals, with a 304 channel SQUID vector magnetometer system in the Berlin Magnetically Shielded Room II. The SQUID system consists of 19 modules, each containing 16 SQUIDs. Of these, 6 are sensitive to the z component of the magnetic field produced by the heart currents and the other 10 to the perpendicular components. Figure 4 illustrates the configuration.

Bottom Line: The latter were recorded simultaneously from the same individuals a few hours after the MRI sessions.A training dataset is made publicly available; datasets for blind testing will remain undisclosed.While the MRI data may provide a common input that can be applied to different numerical heart models, the verification and comparison of different models can be performed by comparing the measured biosignals with forward calculated signals from the models.

View Article: PubMed Central - HTML - PubMed

Affiliation: Physikalisch-Technische Bundesanstalt, Abbestr, 2-12, 10587 Berlin, Germany. hans.koch@ptb.de

ABSTRACT

Background: The evaluation, verification and comparison of different numerical heart models are difficult without a commonly available database that could be utilized as a reference. Our aim was to compile an exemplary dataset.

Methods: The following methods were employed: Magnetic Resonance Imaging (MRI) of heart and torso, Body Surface Potential Maps (BSPM) and MagnetoCardioGraphy (MCG) maps. The latter were recorded simultaneously from the same individuals a few hours after the MRI sessions.

Results: A training dataset is made publicly available; datasets for blind testing will remain undisclosed.

Conclusions: While the MRI data may provide a common input that can be applied to different numerical heart models, the verification and comparison of different models can be performed by comparing the measured biosignals with forward calculated signals from the models.

Show MeSH