AI-driven multicore fiber-optic cell rotation

Research output: Contribution to book/Conference proceedings/Anthology/ReportConference contributionContributedpeer-review

Contributors

  • Jiawei Sun - , Chair of Measurement and Sensor System Technique, Shanghai Artificial Intelligence Laboratory (Author)
  • Zhaoqing Chen - , Shanghai Artificial Intelligence Laboratory (Author)
  • Yuhang Tang - , Shanghai Artificial Intelligence Laboratory, Northwestern Polytechnical University Xian (Author)
  • Bin Yang - , Chair of Measurement and Sensor System Technique, TUD Dresden University of Technology (Author)
  • Zhigang Wang - , Shanghai Artificial Intelligence Laboratory (Author)
  • Guan Huang - , Northwestern Polytechnical University Xian (Author)
  • Bin Zhao - , Shanghai Artificial Intelligence Laboratory, Northwestern Polytechnical University Xian (Author)
  • Xuelong Li - , Shanghai Artificial Intelligence Laboratory, China Telecommunications (Author)
  • Juergen Czarske - , Chair of Measurement and Sensor System Technique, TUD Dresden University of Technology (Author)

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

Original languageEnglish
Title of host publicationEmerging Topics in Artificial Intelligence, ETAI 2024
EditorsGiovanni Volpe, Joana B. Pereira, Daniel Brunner, Aydogan Ozcan
PublisherSPIE - The international society for optics and photonics, Bellingham
ISBN (electronic)9781510678965
Publication statusPublished - 2024
Peer-reviewedYes

Publication series

SeriesProceedings of SPIE - The International Society for Optical Engineering
Volume13118
ISSN0277-786X

Conference

Title2024 Emerging Topics in Artificial Intelligence, ETAI 2024
Duration18 - 23 August 2024
CitySan Diego
CountryUnited States of America

Keywords

Sustainable Development Goals

Keywords

  • Deep learning, Fiber-optic trapping, Optical manipulation, Optical tomography, Quantitative phase imaging