A stable and quantitative method for dimensionality reduction of aortic centerline Article Swipe
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3389/fcvm.2022.940711
Aortic dissection (AD) is a fatal aortic disease with high mortality. Assessing the morphology of the aorta is critical for diagnostic and surgical decisions. Aortic centerline projection methods have been used to evaluate the morphology of the aorta. However, there is a big difference between the current model of primary plane projection (PPP) and the actual shape of individuals, which is not conducive to morphological statistical analysis. Finding a method to compress the three-dimensional information of the aorta into two dimensions is helpful to clinical decision-making. In this paper, the evaluation parameters, including contour length (CL), enclosure area, and the sum of absolute residuals (SAR), were introduced to objectively evaluate the optimal projection plane rather than artificial subjective judgment. Our results showed that the optimal projection plane could be objectively characterized by the three evaluation parameters. As the morphological criterion, SAR is optimal among the three parameters. Compared to the optimal projection plane selected by traditional PPP, our method has better AD discrimination in the analysis of aortic tortuosity, and is conducive to the clinical operation of AD. Thus, it has application prospects for the preprocessing techniques for the geometric morphology analysis of AD.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3389/fcvm.2022.940711
- OA Status
- gold
- Cited By
- 1
- References
- 37
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4293771245
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4293771245Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3389/fcvm.2022.940711Digital Object Identifier
- Title
-
A stable and quantitative method for dimensionality reduction of aortic centerlineWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2022Year of publication
- Publication date
-
2022-08-31Full publication date if available
- Authors
-
Tao Peng, Hongji Pu, Peng Qiu, Han Yang, Ziyue Ju, Hui Ma, Juanlin Zhang, Kexin Chen, Yanqing Zhan, Rui Sheng, Yi Wang, Binshan Zha, Yang Yang, Shu Fang, Xinwu Lu, Jinhua ZhouList of authors in order
- Landing page
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https://doi.org/10.3389/fcvm.2022.940711Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
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https://doi.org/10.3389/fcvm.2022.940711Direct OA link when available
- Concepts
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Tortuosity, Projection (relational algebra), Preprocessor, Dimensionality reduction, Artificial intelligence, Aorta, Plane (geometry), Aortic dissection, Computer science, Medicine, Pattern recognition (psychology), Mathematics, Cardiology, Radiology, Algorithm, Materials science, Geometry, Porosity, Composite materialTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
- Citations by year (recent)
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2024: 1Per-year citation counts (last 5 years)
- References (count)
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37Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.optimal | 111, 124, 142, 150 |
| abstract_inverted_index.primary | 49 |
| abstract_inverted_index.results | 120 |
| abstract_inverted_index.Compared | 147 |
| abstract_inverted_index.However, | 38 |
| abstract_inverted_index.absolute | 102 |
| abstract_inverted_index.analysis | 165, 191 |
| abstract_inverted_index.clinical | 84, 174 |
| abstract_inverted_index.compress | 71 |
| abstract_inverted_index.critical | 18 |
| abstract_inverted_index.evaluate | 32, 109 |
| abstract_inverted_index.selected | 153 |
| abstract_inverted_index.surgical | 22 |
| abstract_inverted_index.Assessing | 11 |
| abstract_inverted_index.analysis. | 66 |
| abstract_inverted_index.conducive | 62, 171 |
| abstract_inverted_index.enclosure | 96 |
| abstract_inverted_index.geometric | 189 |
| abstract_inverted_index.including | 92 |
| abstract_inverted_index.judgment. | 118 |
| abstract_inverted_index.operation | 175 |
| abstract_inverted_index.prospects | 182 |
| abstract_inverted_index.residuals | 103 |
| abstract_inverted_index.artificial | 116 |
| abstract_inverted_index.centerline | 25 |
| abstract_inverted_index.criterion, | 139 |
| abstract_inverted_index.decisions. | 23 |
| abstract_inverted_index.diagnostic | 20 |
| abstract_inverted_index.difference | 43 |
| abstract_inverted_index.dimensions | 80 |
| abstract_inverted_index.dissection | 1 |
| abstract_inverted_index.evaluation | 90, 134 |
| abstract_inverted_index.introduced | 106 |
| abstract_inverted_index.morphology | 13, 34, 190 |
| abstract_inverted_index.mortality. | 10 |
| abstract_inverted_index.projection | 26, 51, 112, 125, 151 |
| abstract_inverted_index.subjective | 117 |
| abstract_inverted_index.techniques | 186 |
| abstract_inverted_index.application | 181 |
| abstract_inverted_index.information | 74 |
| abstract_inverted_index.objectively | 108, 129 |
| abstract_inverted_index.parameters, | 91 |
| abstract_inverted_index.parameters. | 135, 146 |
| abstract_inverted_index.statistical | 65 |
| abstract_inverted_index.tortuosity, | 168 |
| abstract_inverted_index.traditional | 155 |
| abstract_inverted_index.individuals, | 58 |
| abstract_inverted_index.characterized | 130 |
| abstract_inverted_index.morphological | 64, 138 |
| abstract_inverted_index.preprocessing | 185 |
| abstract_inverted_index.discrimination | 162 |
| abstract_inverted_index.decision-making. | 85 |
| abstract_inverted_index.three-dimensional | 73 |
| cited_by_percentile_year.max | 94 |
| cited_by_percentile_year.min | 90 |
| corresponding_author_ids | https://openalex.org/A5113832137, https://openalex.org/A5100528163, https://openalex.org/A5107206111 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 16 |
| corresponding_institution_ids | https://openalex.org/I183067930, https://openalex.org/I197869895, https://openalex.org/I4210097066 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/16 |
| sustainable_development_goals[0].score | 0.6499999761581421 |
| sustainable_development_goals[0].display_name | Peace, Justice and strong institutions |
| citation_normalized_percentile.value | 0.51632441 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |