ArticleJournal of biomedical optics2025
Dual-mode multichannel imaging system for high-throughput live-cell monitoring across large fields of view.
Article in Journal of biomedical optics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
3 authors.
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Abstract
Significance: High-throughput live-cell imaging is crucial for biological applications, including organ-on-a-chip (OoaC) platforms, yet conventional optical systems face a fundamental trade-off between magnification and field of view (FOV). This limitation hinders the ability to capture large-scale biological dynamics while maintaining single-cell resolution. We address this gap by introducing a scalable, high-resolution imaging solution specifically tailored for OoaC platforms and other microfluidic-based systems. Aim: We aim to develop a dual-mode multichannel optical imaging system capable of achieving single-cell resolution over an extended FOV while maintaining a working distance suitable for integration with microfluidic devices. Approach: The system employs microlens arrays in conjunction with laser-fabricated micro-aperture arrays to optically isolate imaging channels, minimizing crosstalk. Two operational modes are implemented: (1) rapid sampling mode for instantaneous, partial-area imaging and (2) full-field imaging mode, utilizing micro-scanning and computational stitching to generate a seamless high-resolution composite. The system's performance was validated through experimental imaging and theoretical modeling. Results: The system achieves an FOV of Conclusions: This compact and scalable imaging system overcomes the traditional magnification-FOV trade-off, offering a powerful tool for drug screening, cellular dynamics studies, and microfluidic-based biological analyses. Its high-resolution capability and adaptability make it a valuable asset for advancing OoaC technologies.
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