Issue |
EPJ Web Conf.
Volume 309, 2024
EOS Annual Meeting (EOSAM 2024)
|
|
---|---|---|
Article Number | 02002 | |
Number of page(s) | 2 | |
Section | Topical Meeting (TOM) 2- Frontiers in Optical Metrology | |
DOI | https://doi.org/10.1051/epjconf/202430902002 | |
Published online | 31 October 2024 |
https://doi.org/10.1051/epjconf/202430902002
In-flow tomographic imaging for single cells analysis
1 CNR-ISASI, Institute of Applied Sciences and Intelligent Systems – Via Campi Flegrei 34, Pozzuoli (NA), Italy
2 DICMaPI, Department of Chemical, Materials and Production Engineering, University of Naples “Federico II”
* Corresponding author: lisa.miccio@cnr.it
Published online: 31 October 2024
Gold standard imaging modalities in biological field are based on fluorescence signals providing high specificity and high resolution. Recently, Fluorescence Microscopy has been combined with microfluidics to develop instrumentations called Imaging Flow Cytometers, high-throughput tools that supply bright-field, darkfield and multiple-channels fluorescence images of each single cell passing in the Field Of View (FOV). Nevertheless, Fluorescence Microscopy has some drawbacks as phototoxicity, photobleaching, expensive costs for sample preparations and also the a-priori knowledge of the tags to be used. For these reasons label-free imaging methods greatly increase in the recent years as the Quantitative Phase Imaging (QPI) technologies for microscopy. One of the optical techniques to achieve QPI is Digital Holography. DH in microscopy has several advantages such as the possibility to numerically scan the focal distance, a properties that open to the integration of DH in microfluidics. Indeed DH combined with microfluidic circuits allows to image particles or cells flowing into the FOV at different depths. Here the capabilities of label-free single-cell imaging by DH are presented and their implications on next future biomedical applications discussed. Static or in-flow configurations will be showed describing recent results and perspectives also in combination with Artificial Intelligence architectures for future applications in biomedical and clinical fields.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.