Estimation of Cardiac Fibre Direction Based on Activation Maps Article Swipe
J. W. de Vries
,
Miao Sun
,
Natasja M.S. de Groot
,
Richard C. Hendriks
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1109/icassp49357.2023.10095692
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1109/icassp49357.2023.10095692
Estimating tissue conductivity parameters from electrograms (EGMs) could be an important tool for diagnosing and treating heart rhythm disorders such as atrial fibrillation (AF). One of these parameters is the fibre direction, often assumed to be known in conductivity estimation methods. In this paper, a novel method to estimate the fibre direction from EGMs is presented. This method is based on local conduction slowness vectors of a propagating activation wave. These conduction slowness vectors follow an elliptical pattern that depends on the underlying conductivity parameters. The fibre direction and conductivity anisotropy ratio can therefore be estimated by fitting an ellipse to the conduction slowness vectors. Applying the presented method on simulated data shows that it can estimate the fibre direction more accurately than existing methods, and that its performance depends mostly on the range of wavefront directions present in the measurement area. The main advantage of the presented method is that it still functions relatively well in the presence of conduction blocks, as long as the surrounding tissue is approximately homogeneous.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/icassp49357.2023.10095692
- OA Status
- green
- Cited By
- 3
- References
- 18
- Related Works
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- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4372339439Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/icassp49357.2023.10095692Digital Object Identifier
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Estimation of Cardiac Fibre Direction Based on Activation MapsWork title
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articleOpenAlex work type
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enPrimary language
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2023Year of publication
- Publication date
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2023-05-05Full publication date if available
- Authors
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J. W. de Vries, Miao Sun, Natasja M.S. de Groot, Richard C. HendriksList of authors in order
- Landing page
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https://doi.org/10.1109/icassp49357.2023.10095692Publisher landing page
- Open access
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greenOpen access status per OpenAlex
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https://repository.tudelft.nl/file/File_ce0b4270-53a1-484a-bc3a-7aeda502419aDirect OA link when available
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Slowness, Thermal conduction, Ellipse, Anisotropy, Wavefront, Conductivity, Mathematics, Biological system, Acoustics, Algorithm, Optics, Physics, Geometry, Quantum mechanics, Biology, ThermodynamicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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3Total citation count in OpenAlex
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2025: 1, 2024: 2Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.main | 143 |
| abstract_inverted_index.more | 120 |
| abstract_inverted_index.such | 19 |
| abstract_inverted_index.than | 122 |
| abstract_inverted_index.that | 78, 113, 126, 150 |
| abstract_inverted_index.this | 42 |
| abstract_inverted_index.tool | 11 |
| abstract_inverted_index.well | 155 |
| abstract_inverted_index.(AF). | 23 |
| abstract_inverted_index.These | 70 |
| abstract_inverted_index.area. | 141 |
| abstract_inverted_index.based | 59 |
| abstract_inverted_index.could | 7 |
| abstract_inverted_index.fibre | 30, 50, 86, 118 |
| abstract_inverted_index.heart | 16 |
| abstract_inverted_index.known | 36 |
| abstract_inverted_index.local | 61 |
| abstract_inverted_index.novel | 45 |
| abstract_inverted_index.often | 32 |
| abstract_inverted_index.range | 133 |
| abstract_inverted_index.ratio | 91 |
| abstract_inverted_index.shows | 112 |
| abstract_inverted_index.still | 152 |
| abstract_inverted_index.these | 26 |
| abstract_inverted_index.wave. | 69 |
| abstract_inverted_index.(EGMs) | 6 |
| abstract_inverted_index.atrial | 21 |
| abstract_inverted_index.follow | 74 |
| abstract_inverted_index.method | 46, 57, 108, 148 |
| abstract_inverted_index.mostly | 130 |
| abstract_inverted_index.paper, | 43 |
| abstract_inverted_index.rhythm | 17 |
| abstract_inverted_index.tissue | 1, 167 |
| abstract_inverted_index.assumed | 33 |
| abstract_inverted_index.blocks, | 161 |
| abstract_inverted_index.depends | 79, 129 |
| abstract_inverted_index.ellipse | 99 |
| abstract_inverted_index.fitting | 97 |
| abstract_inverted_index.pattern | 77 |
| abstract_inverted_index.present | 137 |
| abstract_inverted_index.vectors | 64, 73 |
| abstract_inverted_index.Applying | 105 |
| abstract_inverted_index.estimate | 48, 116 |
| abstract_inverted_index.existing | 123 |
| abstract_inverted_index.methods, | 124 |
| abstract_inverted_index.methods. | 40 |
| abstract_inverted_index.presence | 158 |
| abstract_inverted_index.slowness | 63, 72, 103 |
| abstract_inverted_index.treating | 15 |
| abstract_inverted_index.vectors. | 104 |
| abstract_inverted_index.advantage | 144 |
| abstract_inverted_index.direction | 51, 87, 119 |
| abstract_inverted_index.disorders | 18 |
| abstract_inverted_index.estimated | 95 |
| abstract_inverted_index.functions | 153 |
| abstract_inverted_index.important | 10 |
| abstract_inverted_index.presented | 107, 147 |
| abstract_inverted_index.simulated | 110 |
| abstract_inverted_index.therefore | 93 |
| abstract_inverted_index.wavefront | 135 |
| abstract_inverted_index.Estimating | 0 |
| abstract_inverted_index.accurately | 121 |
| abstract_inverted_index.activation | 68 |
| abstract_inverted_index.anisotropy | 90 |
| abstract_inverted_index.conduction | 62, 71, 102, 160 |
| abstract_inverted_index.diagnosing | 13 |
| abstract_inverted_index.direction, | 31 |
| abstract_inverted_index.directions | 136 |
| abstract_inverted_index.elliptical | 76 |
| abstract_inverted_index.estimation | 39 |
| abstract_inverted_index.parameters | 3, 27 |
| abstract_inverted_index.presented. | 55 |
| abstract_inverted_index.relatively | 154 |
| abstract_inverted_index.underlying | 82 |
| abstract_inverted_index.measurement | 140 |
| abstract_inverted_index.parameters. | 84 |
| abstract_inverted_index.performance | 128 |
| abstract_inverted_index.propagating | 67 |
| abstract_inverted_index.surrounding | 166 |
| abstract_inverted_index.conductivity | 2, 38, 83, 89 |
| abstract_inverted_index.electrograms | 5 |
| abstract_inverted_index.fibrillation | 22 |
| abstract_inverted_index.homogeneous. | 170 |
| abstract_inverted_index.approximately | 169 |
| cited_by_percentile_year.max | 96 |
| cited_by_percentile_year.min | 91 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| citation_normalized_percentile.value | 0.73460053 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |