Cell Detection and Classification
Nanoplanktonic cell imaging
Imaging-in-Flow: Digital holographic microscopy as a novel tool to detect and classify nanoplanktonic organism
E. Zetsche, A. El Mallahi, F. Dubois, C. Yourassowsky, J. C. Kromkamp, F.J.R. Meysman,
Limnol. Oceanogr.: Methods 12, 2014, 757-775 © 2014, by the American Society of Limnology and Oceanography, Inc.
Nanoplanktonic cells similar in shape were successfully detected and classified from images captured with an off-axis digital holographic microscope with partial coherence and a flow-through system based at the Universite Libre de Bruxelles (Belgium). Morphological and textural features of light intensity images were extracted as well as textural features of the phase information images, unique to DHM. An overall classification score of 92.4% demonstrated the potential of holographic-based imaging-in-flow to replace flow cytometry and classical brightfield microscopy for the detection of similar looking organism in the nanoplankton range.
A QMod mounted on a Zeiss Axioplan was used in this study to observe changes of internal cell structures in one of the nanoplanktonic organisms, Chlorella autotrophica, as growth conditions for the culture changed. Phosphate depletion over time in the culture significantly affected the physiology of the cells. Cell detection and feature extraction of images captured with the QMod confirmed that changes occurred within the cells over time, yet that these were minor compared to the differences observed between the three different species. This reiterated the ability of DHM to detect cellular changes and to differentiate species based on the added information gained from phase images.
Figure: False colour rendition of the phase information (optical thickness) from holograms captured with the QMod of (A) cells of the green algae Chlorella autotrophica imaged on day 2 of the phosphate free culturing conditions compared to (B) a cell imaged on day 9 of the experiment when cell physiology was significantly impaired. (Images courtesy of E. Zetsche, unpubl.).
-El Mallahi, A., Minetti, C., & Dubois, F. (2013). Automated three-dimensional detection and classification of living organisms using digital holographic microscopy with partial spatial coherent source: Application to the monitoring of drinking water resources. Applied Optics, 52(1), A68-A80.
- Yourassowsky, C., & Dubois, F. (2014). High throughput holographic imaging-in-flow for the analysis of a wide plankton size range. Optics Express, 22(6), 13. doi:DOI:10.1364/OE.22.006661