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The Consortium for Electrocardiographic Imaging.

Computing in cardiology

Coll-Font J, Dhamala J, Potyagaylo D, Schulze WH, Tate JD, Guillem MS, van Dam P, Dossel O, Brooks DH, Macleod RS.
PMID: 28451592
Comput Cardiol (2010). 2016 Sep;43:325-328. Epub 2017 Mar 02.

Electrocardiographic imaging (ECGI) has recently gained attention as a viable diagnostic tool for reconstructing cardiac electrical activity in normal hearts as well as in cardiac arrhythmias. However, progress has been limited by the lack of both standards and unbiased...

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Coll-Font J, Dhamala J, Potyagaylo D, et al. The Consortium for Electrocardiographic Imaging. Comput Cardiol (2010). 2017;43:325-328
Coll-Font, J., Dhamala, J., Potyagaylo, D., Schulze, W. H., Tate, J. D., Guillem, M. S., van Dam, P., Dossel, O., Brooks, D. H., & Macleod, R. S. (2016). The Consortium for Electrocardiographic Imaging. Computing in cardiology, 43325-328.
Coll-Font, Jaume, et al. "The Consortium for Electrocardiographic Imaging." Computing in cardiology vol. 43 (2016): 325-328.
Coll-Font J, Dhamala J, Potyagaylo D, Schulze WH, Tate JD, Guillem MS, van Dam P, Dossel O, Brooks DH, Macleod RS. The Consortium for Electrocardiographic Imaging. Comput Cardiol (2010). 2016 Sep;43:325-328. Epub 2017 Mar 02. PMID: 28451592; PMCID: PMC5404701.
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Detecting Ischemic Stress to the Myocardium Using Laplacian Eigenmaps and Changes to Conduction Velocity.

Computing in cardiology

Good WW, Erem B, Coll-Font J, Brooks DH, MacLeod RS.
PMID: 29930952
Comput Cardiol (2010). 2017 Sep;44. doi: 10.22489/CinC.2017.269-417. Epub 2018 Apr 05.

The underlying pathophysiology of ischemia and its electrocardiographic consequences are poorly understood, resulting in unreliable diagnosis of this disease. This limited knowledge of underlying mechanisms suggests a data driven approach, which seeks to identify patterns in the ECG that...

Cite
Good WW, Erem B, Coll-Font J, et al. Detecting Ischemic Stress to the Myocardium Using Laplacian Eigenmaps and Changes to Conduction Velocity. Comput Cardiol (2010). 2018;44doi: 10.22489/CinC.2017.269-417.
Good, W. W., Erem, B., Coll-Font, J., Brooks, D. H., & MacLeod, R. S. (2017). Detecting Ischemic Stress to the Myocardium Using Laplacian Eigenmaps and Changes to Conduction Velocity. Computing in cardiology, 44. https://doi.org/10.22489/CinC.2017.269-417
Good, Wilson W, et al. "Detecting Ischemic Stress to the Myocardium Using Laplacian Eigenmaps and Changes to Conduction Velocity." Computing in cardiology vol. 44 (2017). doi: https://doi.org/10.22489/CinC.2017.269-417
Good WW, Erem B, Coll-Font J, Brooks DH, MacLeod RS. Detecting Ischemic Stress to the Myocardium Using Laplacian Eigenmaps and Changes to Conduction Velocity. Comput Cardiol (2010). 2017 Sep;44. doi: 10.22489/CinC.2017.269-417. Epub 2018 Apr 05. PMID: 29930952; PMCID: PMC6007991.
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Spatiotemporal approximation of cardiac activation and recovery isochrones.

Journal of electrocardiology

Cluitmans M, Coll-Font J, Erem B, Bear L, Nguyên UC, Ter Bekke R, Volders PGA, Brooks D.
PMID: 34979408
J Electrocardiol. 2021 Dec 28;71:1-9. doi: 10.1016/j.jelectrocard.2021.12.007. Epub 2021 Dec 28.

BACKGROUND: The sequence of myocardial activation and recovery can be studied in detail by invasive catheter recordings of cardiac electrograms (EGMs), or noninvasive inverse reconstructions thereof with electrocardiographic imaging (ECGI). Local activation and recovery times are obtained from a...

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Cluitmans M, Coll-Font J, Erem B, et al. Spatiotemporal approximation of cardiac activation and recovery isochrones. J Electrocardiol. 2021;71:1-9doi: 10.1016/j.jelectrocard.2021.12.007.
Cluitmans, M., Coll-Font, J., Erem, B., Bear, L., Nguyên, U. C., Ter Bekke, R., Volders, P. G. A., & Brooks, D. (2021). Spatiotemporal approximation of cardiac activation and recovery isochrones. Journal of electrocardiology, 711-9. https://doi.org/10.1016/j.jelectrocard.2021.12.007
Cluitmans, Matthijs, et al. "Spatiotemporal approximation of cardiac activation and recovery isochrones." Journal of electrocardiology vol. 71 (2021): 1-9. doi: https://doi.org/10.1016/j.jelectrocard.2021.12.007
Cluitmans M, Coll-Font J, Erem B, Bear L, Nguyên UC, Ter Bekke R, Volders PGA, Brooks D. Spatiotemporal approximation of cardiac activation and recovery isochrones. J Electrocardiol. 2021 Dec 28;71:1-9. doi: 10.1016/j.jelectrocard.2021.12.007. Epub 2021 Dec 28. PMID: 34979408.
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Spatiotemporal approximation of cardiac activation and recovery isochrones.

Journal of electrocardiology

Cluitmans M, Coll-Font J, Erem B, Bear L, Nguyên UC, Ter Bekke R, Volders PGA, Brooks D.
PMID: 34979408
J Electrocardiol. 2021 Dec 28;71:1-9. doi: 10.1016/j.jelectrocard.2021.12.007. Epub 2021 Dec 28.

BACKGROUND: The sequence of myocardial activation and recovery can be studied in detail by invasive catheter recordings of cardiac electrograms (EGMs), or noninvasive inverse reconstructions thereof with electrocardiographic imaging (ECGI). Local activation and recovery times are obtained from a...

Cite
Cluitmans M, Coll-Font J, Erem B, et al. Spatiotemporal approximation of cardiac activation and recovery isochrones. J Electrocardiol. 2021;71:1-9doi: 10.1016/j.jelectrocard.2021.12.007.
Cluitmans, M., Coll-Font, J., Erem, B., Bear, L., Nguyên, U. C., Ter Bekke, R., Volders, P. G. A., & Brooks, D. (2021). Spatiotemporal approximation of cardiac activation and recovery isochrones. Journal of electrocardiology, 711-9. https://doi.org/10.1016/j.jelectrocard.2021.12.007
Cluitmans, Matthijs, et al. "Spatiotemporal approximation of cardiac activation and recovery isochrones." Journal of electrocardiology vol. 71 (2021): 1-9. doi: https://doi.org/10.1016/j.jelectrocard.2021.12.007
Cluitmans M, Coll-Font J, Erem B, Bear L, Nguyên UC, Ter Bekke R, Volders PGA, Brooks D. Spatiotemporal approximation of cardiac activation and recovery isochrones. J Electrocardiol. 2021 Dec 28;71:1-9. doi: 10.1016/j.jelectrocard.2021.12.007. Epub 2021 Dec 28. PMID: 34979408.
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Simultaneous Multi-Heartbeat ECGI Solution with a Time-Varying Forward Model: a Joint Inverse Formulation.

Functional imaging and modeling of the heart : ... International Workshop, FIMH ..., proceedings. FIMH

Bergquist JA, Coll-Font J, Zenger B, Rupp LC, Good WW, Brooks DH, MacLeod RS.
PMID: 34447971
Funct Imaging Model Heart. 2021 Jun;12738:493-502. doi: 10.1007/978-3-030-78710-3_47. Epub 2021 Jun 18.

Electrocardiographic imaging (ECGI) is an effective tool for noninvasive diagnosis of a range of cardiac dysfunctions. ECGI leverages a model of how cardiac bioelectric sources appear on the torso surface (the forward problem) and uses recorded body surface potential...

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Bergquist JA, Coll-Font J, Zenger B, et al. Simultaneous Multi-Heartbeat ECGI Solution with a Time-Varying Forward Model: a Joint Inverse Formulation. Funct Imaging Model Heart. 2021;12738:493-502doi: 10.1007/978-3-030-78710-3_47.
Bergquist, J. A., Coll-Font, J., Zenger, B., Rupp, L. C., Good, W. W., Brooks, D. H., & MacLeod, R. S. (2021). Simultaneous Multi-Heartbeat ECGI Solution with a Time-Varying Forward Model: a Joint Inverse Formulation. Functional imaging and modeling of the heart : ... International Workshop, FIMH ..., proceedings. FIMH, 12738493-502. https://doi.org/10.1007/978-3-030-78710-3_47
Bergquist, Jake A, et al. "Simultaneous Multi-Heartbeat ECGI Solution with a Time-Varying Forward Model: a Joint Inverse Formulation." Functional imaging and modeling of the heart : ... International Workshop, FIMH ..., proceedings. FIMH vol. 12738 (2021): 493-502. doi: https://doi.org/10.1007/978-3-030-78710-3_47
Bergquist JA, Coll-Font J, Zenger B, Rupp LC, Good WW, Brooks DH, MacLeod RS. Simultaneous Multi-Heartbeat ECGI Solution with a Time-Varying Forward Model: a Joint Inverse Formulation. Funct Imaging Model Heart. 2021 Jun;12738:493-502. doi: 10.1007/978-3-030-78710-3_47. Epub 2021 Jun 18. PMID: 34447971; PMCID: PMC8385662.
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ECG-Based Reconstruction of Heart Position and Orientation with Bayesian Optimization.

Computing in cardiology

Coll-Font J, Ariafar S, Brooks DH.
PMID: 29930951
Comput Cardiol (2010). 2017 Sep;44. doi: 10.22489/CinC.2017.054-387. Epub 2018 Apr 05.

Respiratory motion is known to cause beat-to-beat variation of the ECG. This observation suggests that it may be possible to use this variation to track position and orientation of the heart. Electrocardiographic Imaging (ECGI) would benefit from such a...

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Coll-Font J, Ariafar S, Brooks DH. ECG-Based Reconstruction of Heart Position and Orientation with Bayesian Optimization. Comput Cardiol (2010). 2018;44doi: 10.22489/CinC.2017.054-387.
Coll-Font, J., Ariafar, S., & Brooks, D. H. (2017). ECG-Based Reconstruction of Heart Position and Orientation with Bayesian Optimization. Computing in cardiology, 44. https://doi.org/10.22489/CinC.2017.054-387
Coll-Font, Jaume, et al. "ECG-Based Reconstruction of Heart Position and Orientation with Bayesian Optimization." Computing in cardiology vol. 44 (2017). doi: https://doi.org/10.22489/CinC.2017.054-387
Coll-Font J, Ariafar S, Brooks DH. ECG-Based Reconstruction of Heart Position and Orientation with Bayesian Optimization. Comput Cardiol (2010). 2017 Sep;44. doi: 10.22489/CinC.2017.054-387. Epub 2018 Apr 05. PMID: 29930951; PMCID: PMC6007986.
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Comparison of Activation Times Estimation for Potential-Based ECG Imaging.

Computing in cardiology

Schaufelberger M, Schuler S, Bear L, Cluitmans M, Coll-Font J, Onak ÖN, Dössel O, Brooks D.
PMID: 32190705
Comput Cardiol (2010). 2019 Sep;46. doi: 10.22489/cinc.2019.379. Epub 2020 Feb 24.

Activation times (AT) describe the sequence of cardiac depolarization and represent one of the most important parameters for analysis of cardiac electrical activity. However, estimation of ATs can be challenging due to multiple sources of noise such as fractionation...

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Schaufelberger M, Schuler S, Bear L, et al. Comparison of Activation Times Estimation for Potential-Based ECG Imaging. Comput Cardiol (2010). 2020;46doi: 10.22489/cinc.2019.379.
Schaufelberger, M., Schuler, S., Bear, L., Cluitmans, M., Coll-Font, J., Onak, �. �. N., Dössel, O., & Brooks, D. (2019). Comparison of Activation Times Estimation for Potential-Based ECG Imaging. Computing in cardiology, 46. https://doi.org/10.22489/cinc.2019.379
Schaufelberger, Matthias, et al. "Comparison of Activation Times Estimation for Potential-Based ECG Imaging." Computing in cardiology vol. 46 (2019). doi: https://doi.org/10.22489/cinc.2019.379
Schaufelberger M, Schuler S, Bear L, Cluitmans M, Coll-Font J, Onak ÖN, Dössel O, Brooks D. Comparison of Activation Times Estimation for Potential-Based ECG Imaging. Comput Cardiol (2010). 2019 Sep;46. doi: 10.22489/cinc.2019.379. Epub 2020 Feb 24. PMID: 32190705; PMCID: PMC7079739.
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New Additions to the Toolkit for Forward/Inverse Problems in Electrocardiography within the SCIRun Problem Solving Environment.

Computing in cardiology

Coll-Font J, Burton BM, Tate JD, Erem B, Swenson DJ, Wang D, Brooks DH, van Dam P, Macleod RS.
PMID: 26618184
Comput Cardiol (2010). 2014 Sep;2014:213-216.

Cardiac electrical imaging often requires the examination of different forward and inverse problem formulations based on mathematical and numerical approximations of the underlying source and the intervening volume conductor that can generate the associated voltages on the surface of...

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Coll-Font J, Burton BM, Tate JD, et al. New Additions to the Toolkit for Forward/Inverse Problems in Electrocardiography within the SCIRun Problem Solving Environment. Comput Cardiol (2010). 2014;2014:213-216
Coll-Font, J., Burton, B. M., Tate, J. D., Erem, B., Swenson, D. J., Wang, D., Brooks, D. H., van Dam, P., & Macleod, R. S. (2014). New Additions to the Toolkit for Forward/Inverse Problems in Electrocardiography within the SCIRun Problem Solving Environment. Computing in cardiology, 2014213-216.
Coll-Font, Jaume, et al. "New Additions to the Toolkit for Forward/Inverse Problems in Electrocardiography within the SCIRun Problem Solving Environment." Computing in cardiology vol. 2014 (2014): 213-216.
Coll-Font J, Burton BM, Tate JD, Erem B, Swenson DJ, Wang D, Brooks DH, van Dam P, Macleod RS. New Additions to the Toolkit for Forward/Inverse Problems in Electrocardiography within the SCIRun Problem Solving Environment. Comput Cardiol (2010). 2014 Sep;2014:213-216. PMID: 26618184; PMCID: PMC4662553.
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Linear Time Invariant Model based Motion Correction (LiMo-MoCo) of Dynamic Radial Contrast Enhanced MRI.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention

Coll-Font J, Afacan O, Chow J, Kurugol S.
PMID: 32483560
Med Image Comput Comput Assist Interv. 2019 Oct;11765:430-437. doi: 10.1007/978-3-030-32245-8_48. Epub 2019 Oct 10.

Early identification of kidney function deterioration is essential to determine which newborn patients with dilation of the renal pelvis (hydronephrosis) should undergo surgery. Kidney function can be measured by fitting a tracer kinetic (TK) model onto a series of...

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Coll-Font J, Afacan O, Chow J, et al. Linear Time Invariant Model based Motion Correction (LiMo-MoCo) of Dynamic Radial Contrast Enhanced MRI. Med Image Comput Comput Assist Interv. 2019;11765:430-437doi: 10.1007/978-3-030-32245-8_48.
Coll-Font, J., Afacan, O., Chow, J., & Kurugol, S. (2019). Linear Time Invariant Model based Motion Correction (LiMo-MoCo) of Dynamic Radial Contrast Enhanced MRI. Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, 11765430-437. https://doi.org/10.1007/978-3-030-32245-8_48
Coll-Font, Jaume, et al. "Linear Time Invariant Model based Motion Correction (LiMo-MoCo) of Dynamic Radial Contrast Enhanced MRI." Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention vol. 11765 (2019): 430-437. doi: https://doi.org/10.1007/978-3-030-32245-8_48
Coll-Font J, Afacan O, Chow J, Kurugol S. Linear Time Invariant Model based Motion Correction (LiMo-MoCo) of Dynamic Radial Contrast Enhanced MRI. Med Image Comput Comput Assist Interv. 2019 Oct;11765:430-437. doi: 10.1007/978-3-030-32245-8_48. Epub 2019 Oct 10. PMID: 32483560; PMCID: PMC7262873.
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Novel Metric Using Laplacian Eigenmaps to Evaluate Ischemic Stress on the Torso Surface.

Computing in cardiology

Good WW, Erem B, Coll-Font J, Zenger B, Horáček BM, Brooks DH, MacLeod RS.
PMID: 31338374
Comput Cardiol (2010). 2018 Sep;45. doi: 10.22489/CinC.2018.351. Epub 2019 Jun 24.

The underlying pathophysiology of myocardial ischemia is incompletely understood, resulting in persistent difficulty of diagnosis. This limited understanding of underlying mechanisms encourages a data driven approach, which seeks to identify patterns in the ECG data that can be linked...

Cite
Good WW, Erem B, Coll-Font J, et al. Novel Metric Using Laplacian Eigenmaps to Evaluate Ischemic Stress on the Torso Surface. Comput Cardiol (2010). 2019;45doi: 10.22489/CinC.2018.351.
Good, W. W., Erem, B., Coll-Font, J., Zenger, B., Horáček, B. M., Brooks, D. H., & MacLeod, R. S. (2018). Novel Metric Using Laplacian Eigenmaps to Evaluate Ischemic Stress on the Torso Surface. Computing in cardiology, 45. https://doi.org/10.22489/CinC.2018.351
Good, Wilson W, et al. "Novel Metric Using Laplacian Eigenmaps to Evaluate Ischemic Stress on the Torso Surface." Computing in cardiology vol. 45 (2018). doi: https://doi.org/10.22489/CinC.2018.351
Good WW, Erem B, Coll-Font J, Zenger B, Horáček BM, Brooks DH, MacLeod RS. Novel Metric Using Laplacian Eigenmaps to Evaluate Ischemic Stress on the Torso Surface. Comput Cardiol (2010). 2018 Sep;45. doi: 10.22489/CinC.2018.351. Epub 2019 Jun 24. PMID: 31338374; PMCID: PMC6648695.
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Improving Localization of Cardiac Geometry Using ECGI.

Computing in cardiology

Bergquist JA, Coll-Font J, Zenger B, Rupp LC, Good WW, Brooks DH, MacLeod RS.
PMID: 33937429
Comput Cardiol (2010). 2020 Sep;47. doi: 10.22489/cinc.2020.273. Epub 2021 Feb 10.

INTRODUCTION: Electrocardiographic imaging (ECGI) requires a model of the torso, and inaccuracy in the position of the heart is a known source of error. We previously presented a method to localize the heart when body and heart surface potentials...

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Bergquist JA, Coll-Font J, Zenger B, et al. Improving Localization of Cardiac Geometry Using ECGI. Comput Cardiol (2010). 2021;47doi: 10.22489/cinc.2020.273.
Bergquist, J. A., Coll-Font, J., Zenger, B., Rupp, L. C., Good, W. W., Brooks, D. H., & MacLeod, R. S. (2020). Improving Localization of Cardiac Geometry Using ECGI. Computing in cardiology, 47. https://doi.org/10.22489/cinc.2020.273
Bergquist, Jake A, et al. "Improving Localization of Cardiac Geometry Using ECGI." Computing in cardiology vol. 47 (2020). doi: https://doi.org/10.22489/cinc.2020.273
Bergquist JA, Coll-Font J, Zenger B, Rupp LC, Good WW, Brooks DH, MacLeod RS. Improving Localization of Cardiac Geometry Using ECGI. Comput Cardiol (2010). 2020 Sep;47. doi: 10.22489/cinc.2020.273. Epub 2021 Feb 10. PMID: 33937429; PMCID: PMC8082332.
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Spatiotemporal approximation of cardiac activation and recovery isochrones.

Journal of electrocardiology

Cluitmans M, Coll-Font J, Erem B, Bear L, Nguyên UC, Ter Bekke R, Volders PGA, Brooks D.
PMID: 34979408
J Electrocardiol. 2021 Dec 28;71:1-9. doi: 10.1016/j.jelectrocard.2021.12.007. Epub 2021 Dec 28.

BACKGROUND: The sequence of myocardial activation and recovery can be studied in detail by invasive catheter recordings of cardiac electrograms (EGMs), or noninvasive inverse reconstructions thereof with electrocardiographic imaging (ECGI). Local activation and recovery times are obtained from a...

Cite
Cluitmans M, Coll-Font J, Erem B, et al. Spatiotemporal approximation of cardiac activation and recovery isochrones. J Electrocardiol. 2021;71:1-9doi: 10.1016/j.jelectrocard.2021.12.007.
Cluitmans, M., Coll-Font, J., Erem, B., Bear, L., Nguyên, U. C., Ter Bekke, R., Volders, P. G. A., & Brooks, D. (2021). Spatiotemporal approximation of cardiac activation and recovery isochrones. Journal of electrocardiology, 711-9. https://doi.org/10.1016/j.jelectrocard.2021.12.007
Cluitmans, Matthijs, et al. "Spatiotemporal approximation of cardiac activation and recovery isochrones." Journal of electrocardiology vol. 71 (2021): 1-9. doi: https://doi.org/10.1016/j.jelectrocard.2021.12.007
Cluitmans M, Coll-Font J, Erem B, Bear L, Nguyên UC, Ter Bekke R, Volders PGA, Brooks D. Spatiotemporal approximation of cardiac activation and recovery isochrones. J Electrocardiol. 2021 Dec 28;71:1-9. doi: 10.1016/j.jelectrocard.2021.12.007. Epub 2021 Dec 28. PMID: 34979408.
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Showing 1 to 12 of 31 entries