Literature DB >> 31632991

Effect of Segmentation Variation on ECG Imaging.

Jess D Tate1, Nejib Zemzemi2, Wilson W Good1, Peter van Dam3, Dana H Brooks4, Rob S MacLeod1.   

Abstract

ECG imaging (ECGI) is the process of calculating electrical cardiac activity from body surface recordings from the geometry and conductivity of the torso volume. A key first step to create geometric models for ECGI and a possible source of considerable variability is to segment the surface of the heart. We hypothesize that this variation in cardiac segmentation will produce variation in the computed ventricular surface potentials from ECGI. To evaluate this hypothesis, we leveraged the resources of the Consortium for ECG Imaging (CEI) to carry out a comparison of ECGI results from the same body surface potentials and multiple ventricular segmentations. We found that using the different segmentations produced variability in the computed ventricular surface potentials. Not surprisingly, locations of greater variance in the computed potential correlated to locations of greater variance in the segmentations, for example near the pulmonary artery and basal anterior left ventricular wall. Our results indicate that ECGI may be more sensitive to segmentation errors on the anterior epicardial surface than on other areas of the heart.

Entities:  

Year:  2018        PMID: 31632991      PMCID: PMC6800733          DOI: 10.22489/CinC.2018.374

Source DB:  PubMed          Journal:  Comput Cardiol (2010)        ISSN: 2325-887X


  8 in total

1.  Simultaneous truth and performance level estimation (STAPLE): an algorithm for the validation of image segmentation.

Authors:  Simon K Warfield; Kelly H Zou; William M Wells
Journal:  IEEE Trans Med Imaging       Date:  2004-07       Impact factor: 10.048

Review 2.  The forward and inverse problems of electrocardiography.

Authors:  R M Gulrajani
Journal:  IEEE Eng Med Biol Mag       Date:  1998 Sep-Oct

3.  Relating epicardial to body surface potential distributions by means of transfer coefficients based on geometry measurements.

Authors:  R C Barr; M Ramsey; M S Spach
Journal:  IEEE Trans Biomed Eng       Date:  1977-01       Impact factor: 4.538

4.  Cardiac position sensitivity study in the electrocardiographic forward problem using stochastic collocation and boundary element methods.

Authors:  Darrell J Swenson; Sarah E Geneser; Jeroen G Stinstra; Robert M Kirby; Rob S MacLeod
Journal:  Ann Biomed Eng       Date:  2011-09-10       Impact factor: 3.934

5.  A toolkit for forward/inverse problems in electrocardiography within the SCIRun problem solving environment.

Authors:  Brett M Burton; Jess D Tate; Burak Erem; Darrell J Swenson; Dafang F Wang; Michael Steffen; Dana H Brooks; Peter M van Dam; Rob S Macleod
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2011

6.  Experimental Data and Geometric Analysis Repository-EDGAR.

Authors:  Kedar Aras; Wilson Good; Jess Tate; Brett Burton; Dana Brooks; Jaume Coll-Font; Olaf Doessel; Walther Schulze; Danila Potyagaylo; Linwei Wang; Peter van Dam; Rob MacLeod
Journal:  J Electrocardiol       Date:  2015-08-04       Impact factor: 1.438

7.  Inverse solution mapping of epicardial potentials: quantitative comparison with epicardial contact mapping.

Authors:  John L Sapp; Fady Dawoud; John C Clements; B Milan Horácek
Journal:  Circ Arrhythm Electrophysiol       Date:  2012-08-24

8.  Overcoming Barriers to Quantification and Comparison of Electrocardiographic Imaging Methods: A Community-Based Approach.

Authors:  Sandesh Ghimire; Jwala Dhamala; Jaume Coll-Font; Jess D Tate; Maria S Guillem; Dana H Brooks; Rob S MacLeod; Linwei Wang
Journal:  Comput Cardiol (2010)       Date:  2018-04-05
  8 in total
  5 in total

1.  Space-time shape uncertainties in the forward and inverse problem of electrocardiography.

Authors:  Lia Gander; Rolf Krause; Michael Multerer; Simone Pezzuto
Journal:  Int J Numer Method Biomed Eng       Date:  2021-09-08       Impact factor: 2.648

2.  A Cardiac Shape Model for Segmentation Uncertainty Quantification.

Authors:  Jess D Tate; Shireen Elhabian; Nejib Zemzemi; Wilson W Good; Peter van Dam; Dana H Brooks; Rob S MacLeod
Journal:  Comput Cardiol (2010)       Date:  2021-09

3.  Uncertainty Quantification of the Effects of Segmentation Variability in ECGI.

Authors:  Jess D Tate; Wilson Good; Nejib Zemzemi; Machteld Boonstra; Peter van Dam; Dana H Brooks; Akil Narayan; Rob S MacLeod
Journal:  Funct Imaging Model Heart       Date:  2021-06-18

4.  Correcting Undersampled Cardiac Sources in Equivalent Double Layer Forward Simulations.

Authors:  Jess D Tate; Steffen Schuler; Olaf Dössel; Rob S MacLeod; Thom F Oostendorp
Journal:  Funct Imaging Model Heart       Date:  2019-05-30

5.  Automated Framework for the Inclusion of a His-Purkinje System in Cardiac Digital Twins of Ventricular Electrophysiology.

Authors:  Karli Gillette; Matthias A F Gsell; Julien Bouyssier; Anton J Prassl; Aurel Neic; Edward J Vigmond; Gernot Plank
Journal:  Ann Biomed Eng       Date:  2021-08-24       Impact factor: 3.934

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.