Three-stage full-wave simulation architecture for in-depth analysis of microspheres in microscopy Article Swipe
Li-Yu Yu
,
Zih-Rou Cyue
,
Guo-Dung J. Su
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1364/oe.381526
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1364/oe.381526
Over a decade, considerable development has been achieved in microsphere microscopy; the popularity of this method is attributable to its compatibility with biomedical applications. Although microscopy has been used extensively, insufficient analyses and simulation approaches capable of explaining the experimental observations have hampered its theoretical development. In this paper, a three-stage full-wave simulation architecture has been presented for the in-depth analysis of the imaging properties of microspheres. This simulation architecture consists of forward and backward propagation mechanisms, following the concept of geometric optics and strictly complying to wave optics at each stage. Three numerical simulation methods, including FDTD, NTFF, and ASPW, are integrated into this simulation architecture to encompass near-field and far-field behaviors and relieve the computational burden. We validated this architecture by comparing our simulation results with the experimental data provided in literature. The results confirmed that the proposed architecture exhibits high consistency both qualitatively and quantitatively. By using this architecture, we demonstrated the near-field effect of the samples on the resolution and provided evidence to explain the conflicts in literature. Moreover, the flexibility and versatility of the proposed architecture in modeling allow adaptation to various scenarios in microsphere microscopy. The results of this study, as an imaging analysis and system design platform, may facilitate the development of microsphere microscopy for biomedical imaging, wafer inspection, and other potential applications.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1364/oe.381526
- OA Status
- gold
- Cited By
- 7
- References
- 26
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3006668468
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3006668468Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1364/oe.381526Digital Object Identifier
- Title
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Three-stage full-wave simulation architecture for in-depth analysis of microspheres in microscopyWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2020Year of publication
- Publication date
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2020-02-16Full publication date if available
- Authors
-
Li-Yu Yu, Zih-Rou Cyue, Guo-Dung J. SuList of authors in order
- Landing page
-
https://doi.org/10.1364/oe.381526Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1364/oe.381526Direct OA link when available
- Concepts
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Computer science, Microscopy, Optics, Architecture, Finite-difference time-domain method, Physics, Art, Visual artsTop concepts (fields/topics) attached by OpenAlex
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7Total citation count in OpenAlex
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2025: 1, 2024: 1, 2023: 1, 2022: 2, 2021: 1Per-year citation counts (last 5 years)
- References (count)
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26Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.paper, | 48 |
| abstract_inverted_index.stage. | 91 |
| abstract_inverted_index.study, | 195 |
| abstract_inverted_index.system | 201 |
| abstract_inverted_index.burden. | 117 |
| abstract_inverted_index.capable | 35 |
| abstract_inverted_index.concept | 79 |
| abstract_inverted_index.decade, | 2 |
| abstract_inverted_index.explain | 167 |
| abstract_inverted_index.forward | 72 |
| abstract_inverted_index.imaging | 63, 198 |
| abstract_inverted_index.relieve | 114 |
| abstract_inverted_index.results | 126, 135, 192 |
| abstract_inverted_index.samples | 159 |
| abstract_inverted_index.various | 186 |
| abstract_inverted_index.Although | 24 |
| abstract_inverted_index.achieved | 7 |
| abstract_inverted_index.analyses | 31 |
| abstract_inverted_index.analysis | 60, 199 |
| abstract_inverted_index.backward | 74 |
| abstract_inverted_index.consists | 70 |
| abstract_inverted_index.evidence | 165 |
| abstract_inverted_index.exhibits | 141 |
| abstract_inverted_index.hampered | 42 |
| abstract_inverted_index.imaging, | 213 |
| abstract_inverted_index.in-depth | 59 |
| abstract_inverted_index.methods, | 95 |
| abstract_inverted_index.modeling | 182 |
| abstract_inverted_index.proposed | 139, 179 |
| abstract_inverted_index.provided | 131, 164 |
| abstract_inverted_index.strictly | 84 |
| abstract_inverted_index.Moreover, | 172 |
| abstract_inverted_index.behaviors | 112 |
| abstract_inverted_index.comparing | 123 |
| abstract_inverted_index.complying | 85 |
| abstract_inverted_index.confirmed | 136 |
| abstract_inverted_index.conflicts | 169 |
| abstract_inverted_index.encompass | 108 |
| abstract_inverted_index.far-field | 111 |
| abstract_inverted_index.following | 77 |
| abstract_inverted_index.full-wave | 51 |
| abstract_inverted_index.geometric | 81 |
| abstract_inverted_index.including | 96 |
| abstract_inverted_index.numerical | 93 |
| abstract_inverted_index.platform, | 203 |
| abstract_inverted_index.potential | 218 |
| abstract_inverted_index.presented | 56 |
| abstract_inverted_index.scenarios | 187 |
| abstract_inverted_index.validated | 119 |
| abstract_inverted_index.adaptation | 184 |
| abstract_inverted_index.approaches | 34 |
| abstract_inverted_index.biomedical | 22, 212 |
| abstract_inverted_index.explaining | 37 |
| abstract_inverted_index.facilitate | 205 |
| abstract_inverted_index.integrated | 102 |
| abstract_inverted_index.microscopy | 25, 210 |
| abstract_inverted_index.near-field | 109, 155 |
| abstract_inverted_index.popularity | 12 |
| abstract_inverted_index.properties | 64 |
| abstract_inverted_index.resolution | 162 |
| abstract_inverted_index.simulation | 33, 52, 68, 94, 105, 125 |
| abstract_inverted_index.consistency | 143 |
| abstract_inverted_index.development | 4, 207 |
| abstract_inverted_index.flexibility | 174 |
| abstract_inverted_index.inspection, | 215 |
| abstract_inverted_index.literature. | 133, 171 |
| abstract_inverted_index.mechanisms, | 76 |
| abstract_inverted_index.microscopy. | 190 |
| abstract_inverted_index.microscopy; | 10 |
| abstract_inverted_index.microsphere | 9, 189, 209 |
| abstract_inverted_index.propagation | 75 |
| abstract_inverted_index.theoretical | 44 |
| abstract_inverted_index.three-stage | 50 |
| abstract_inverted_index.versatility | 176 |
| abstract_inverted_index.architecture | 53, 69, 106, 121, 140, 180 |
| abstract_inverted_index.attributable | 17 |
| abstract_inverted_index.considerable | 3 |
| abstract_inverted_index.demonstrated | 153 |
| abstract_inverted_index.development. | 45 |
| abstract_inverted_index.experimental | 39, 129 |
| abstract_inverted_index.extensively, | 29 |
| abstract_inverted_index.insufficient | 30 |
| abstract_inverted_index.observations | 40 |
| abstract_inverted_index.applications. | 23, 219 |
| abstract_inverted_index.architecture, | 151 |
| abstract_inverted_index.compatibility | 20 |
| abstract_inverted_index.computational | 116 |
| abstract_inverted_index.microspheres. | 66 |
| abstract_inverted_index.qualitatively | 145 |
| abstract_inverted_index.quantitatively. | 147 |
| cited_by_percentile_year.max | 96 |
| cited_by_percentile_year.min | 89 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 3 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/9 |
| sustainable_development_goals[0].score | 0.4099999964237213 |
| sustainable_development_goals[0].display_name | Industry, innovation and infrastructure |
| citation_normalized_percentile.value | 0.57603192 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |