Evidence map›Paper›PMID 31799512›Full record

ArticleFunctional imaging and modeling of the heart : ... International Workshop, FIMH ..., proceedings. FIMH (Conference)2019

GRÖMeR: A Pipeline for Geodesic Refinement of Mesh Registration.

Jake A Bergquist, Wilson W Good, Brian Zenger, Jess D Tate, Rob S MacLeod

Abstract read
In one paragraph

Article in Functional imaging and modeling of the heart : ... International Workshop, FIMH ..., proceedings. FIMH (Conference), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. The electrocardiographic forward problem: A benchmark study.Computers in biology and medicine · 2021
    Article
  6. 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 (Conference) · 2021
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Jake A BergquistUniversity of Utah, Salt Lake City, UT 84112, USA.ORCID 0000-0002-4586-6911
Wilson W GoodUniversity of Utah, Salt Lake City, UT 84112, USA.ORCID 0000-0002-0111-9076
Brian ZengerUniversity of Utah, Salt Lake City, UT 84112, USA.ORCID 0000-0002-0039-9184
Jess D TateUniversity of Utah, Salt Lake City, UT 84112, USA.ORCID 0000-0002-2934-1453
Rob S MacLeodUniversity of Utah, Salt Lake City, UT 84112, USA.ORCID 0000-0002-0000-0356

Funding

TRD - VisualizationP41GM103545 · NIGMS · UNIVERSITY OF UTAH · PI JURRUS, ELIZABETH · 2012 to 2019
$9.7M
NIGMS NIH HHS P41 GM103545
6 · The paper itself

Abstract

The electrical signals produced by the heart can be used to assess cardiac health and diagnose adverse pathologies. Experiments on large mammals provide essential sources of these signals through measurements of up to 1000 simultaneous, distributed locations throughout the heart and torso. To perform accurate spatial analysis of the resulting electrical recordings, researchers must register the locations of each electrode, typically by defining correspondence points from post-experiment, three-dimensional imaging, and directly measured surface electrodes. Often, due to the practical limitations of the experimental situation, only a subset of the electrode locations can be measured, from which the rest must be estimated. We have developed a pipeline, GRÖMeR, that can perform registration of cardiac surface electrode arrays given a limited correspondence point set. This pipeline accounts for global deformations and uses a modified iterative closest points algorithm followed by a geodesically constrained radial basis deformation to calculate a smooth, correspondence-driven registration. To assess the performance of this pipeline, we generated a series of target geometries and limited correspondence patterns based on experimental scenarios. We found that the best performing correspondence pattern required only 20, approximately uniformly distributed points over the epicardial surface of the heart. This study demonstrated the GRÖMeR pipeline to be an accurate and effective way to register cardiac sock electrode arrays from limited correspondence points.

Indexed as

GeodesicRegistrationSurface meshes

Identifiers

PMID31799512
PMCPMC6889814

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.