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정웅규

Jung, Woonggyu
Translational Biophotonics Lab.
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dc.citation.conferencePlace US -
dc.citation.title SPIE Photonics West 2022 -
dc.contributor.author Lee, EunJi -
dc.contributor.author Lee, Sangjin -
dc.contributor.author Yang, Hyunmo -
dc.contributor.author Ahn, Yujin -
dc.contributor.author Park, Kibeom -
dc.contributor.author Kim, Myung-Ju -
dc.contributor.author Aimakov, Nurbolat -
dc.contributor.author Eom, Joo Beom -
dc.contributor.author Jung, Woonggyu -
dc.date.accessioned 2024-01-31T21:05:55Z -
dc.date.available 2024-01-31T21:05:55Z -
dc.date.created 2022-01-26 -
dc.date.issued 2022-01-24 -
dc.description.abstract Histological optical imaging is a gold standard method to observe biological tissues. However, this technique is a time-consuming and labor-intensive process. In this study, we introduce the new approach for digital histopathology which is based on OCM and deep learning. We developed a fully automated multi-scale OCM system equipped with user-friendly operating software and a deep learning module. Various tissues including the cancer model were imaged by OCM, which was further virtually stained. In conclusion, our system offers an efficient process in terms of acquisition time, digitalization and interpretation -
dc.identifier.bibliographicCitation SPIE Photonics West 2022 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/76391 -
dc.publisher The international society for optics and photonics (SPIE) -
dc.title Digital histopathology using optical coherence microscopy(OCM) and deep learning -
dc.type Conference Paper -
dc.date.conferenceDate 2022-01-22 -

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