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Open-top two-photon light sheet microscopy for three-dimensional tissue examination
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Park, Won Yeong | - |
| dc.contributor.author | Yun, Jieun | - |
| dc.contributor.author | Shin, Jinho | - |
| dc.contributor.author | Oh, Byung Ho | - |
| dc.contributor.author | Yoon, Gilsuk | - |
| dc.contributor.author | Hong, Seung-Mo | - |
| dc.contributor.author | Kim, Ki Hean | - |
| dc.date.accessioned | 2025-02-03T08:51:34Z | - |
| dc.date.available | 2025-02-03T08:51:34Z | - |
| dc.date.created | 2025-07-08 | - |
| dc.date.issued | 2024-02 | - |
| dc.identifier.issn | 0277-786X | - |
| dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/201935 | - |
| dc.description.abstract | Nondestructive three-dimensional (3D) pathology based on high-throughput 3D microscopy holds promise as a complement to traditional hematoxylin and eosin (H&E) stained slide-based two-dimensional (2D) pathology by providing rapid 3D pathological information. However, conventional techniques provided superficial information only due to shallow imaging depth. Herein, we developed open-top two-photon light sheet microscopy (OT-TPLSM) for intraoperative 3D pathology. A two-photon excitation light sheet, generated by 1D scanning of a Bessel beam illuminated the sample and planar imaging was conducted at 400 frames/s max. An imaging depth of 60-100 µm was achieved with long excitation wavelengths, and the image throughput was up to 1 cm2 per 7 min. Cells and extra-cellular matrix were visualized using extrinsic fluorescence and intrinsic second harmonic generation, respectively. OT-TPLSM was tested in various human cancer specimens and cancer structures were detected via 3D visualization. OT-TPLSM may have the potential for rapid and precise 3D histopathological examination. © 2024 SPIE. | - |
| dc.description.statementOfResponsibility | restriction | - |
| dc.language | English | - |
| dc.publisher | The International Society for Optical Engineering | - |
| dc.relation.isPartOf | Proceedings of SPIE - The International Society for Optical Engineering | - |
| dc.relation.isPartOf | Proceedings of SPIE--the International Society for Optical Engineering | - |
| dc.rights | CC BY-NC-ND 2.0 KR | - |
| dc.title | Open-top two-photon light sheet microscopy for three-dimensional tissue examination | - |
| dc.type | Article | - |
| dc.contributor.college | College of Medicine (의과대학) | - |
| dc.contributor.department | Dept. of Dermatology (피부과학교실) | - |
| dc.contributor.googleauthor | Park, Won Yeong | - |
| dc.contributor.googleauthor | Yun, Jieun | - |
| dc.contributor.googleauthor | Shin, Jinho | - |
| dc.contributor.googleauthor | Oh, Byung Ho | - |
| dc.contributor.googleauthor | Yoon, Gilsuk | - |
| dc.contributor.googleauthor | Hong, Seung-Mo | - |
| dc.contributor.googleauthor | Kim, Ki Hean | - |
| dc.identifier.doi | 10.1117/12.3016904 | - |
| dc.relation.journalcode | J03800 | - |
| dc.identifier.eissn | 1996-756X | - |
| dc.subject.keyword | 3D imaging | - |
| dc.subject.keyword | 3D pathology | - |
| dc.subject.keyword | Bessel beam illumination | - |
| dc.subject.keyword | nondestructive pathology | - |
| dc.subject.keyword | two-photon light sheet microscopy | - |
| dc.subject.keyword | unsupervised deep learning | - |
| dc.contributor.alternativeName | Oh, Byung Ho | - |
| dc.contributor.affiliatedAuthor | Oh, Byung Ho | - |
| dc.identifier.scopusid | 2-s2.0-85187546241 | - |
| dc.citation.volume | 13076 | - |
| dc.identifier.bibliographicCitation | Proceedings of SPIE - The International Society for Optical Engineering, Vol.13076, 2024-02 | - |
| dc.identifier.rimsid | 87536 | - |
| dc.type.rims | ART | - |
| dc.description.journalClass | 1 | - |
| dc.description.journalClass | 1 | - |
| dc.subject.keywordAuthor | 3D imaging | - |
| dc.subject.keywordAuthor | 3D pathology | - |
| dc.subject.keywordAuthor | Bessel beam illumination | - |
| dc.subject.keywordAuthor | nondestructive pathology | - |
| dc.subject.keywordAuthor | two-photon light sheet microscopy | - |
| dc.subject.keywordAuthor | unsupervised deep learning | - |
| dc.type.docType | Conference paper | - |
| dc.description.isOpenAccess | N | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.identifier.articleno | 1307603 | - |
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