AI-driven multicore fiber-optic cell rotation
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Beitragende
Abstract
Optical manipulation and tomographic imaging play critical roles in biomedical applications, however, applying these technologies to hard-to-reach regions remains challenging. We introduce a series of innovative AI-driven methods designed to facilitate both high-fidelity light field control and image reconstruction through a multicore fiber-optic system. Our approach enables precise, controlled rotation of human cancer cells around all three axes, enabling 3D tomographic reconstructions of these cells with isotropic resolution. The integration of these advanced optical and computational techniques culminates in a powerful optical fiber probe, capable of sophisticated optical manipulation and tomographic imaging, offering new perspectives for optical manipulation and its applications.
Details
Originalsprache | Englisch |
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Titel | Emerging Topics in Artificial Intelligence, ETAI 2024 |
Redakteure/-innen | Giovanni Volpe, Joana B. Pereira, Daniel Brunner, Aydogan Ozcan |
Herausgeber (Verlag) | SPIE - The international society for optics and photonics, Bellingham |
ISBN (elektronisch) | 9781510678965 |
Publikationsstatus | Veröffentlicht - 2024 |
Peer-Review-Status | Ja |
Publikationsreihe
Reihe | Proceedings of SPIE - The International Society for Optical Engineering |
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Band | 13118 |
ISSN | 0277-786X |
Konferenz
Titel | 2024 Emerging Topics in Artificial Intelligence, ETAI 2024 |
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Dauer | 18 - 23 August 2024 |
Stadt | San Diego |
Land | USA/Vereinigte Staaten |
Schlagworte
Ziele für nachhaltige Entwicklung
ASJC Scopus Sachgebiete
Schlagwörter
- Deep learning, Fiber-optic trapping, Optical manipulation, Optical tomography, Quantitative phase imaging