Optical cell sorting with multiple imaging modalities

Andrew Bañas; Caro Carrissemoux; Mark Villangca; Darwin Palima; Jesper Glückstad

doi:10.1117/12.2254358

27 February 2017 Optical cell sorting with multiple imaging modalities

Andrew Bañas, Caro Carrissemoux, Mark Villangca, Darwin Palima, Jesper Glückstad

Proceedings Volume 10120, Complex Light and Optical Forces XI; 1012018 (2017) https://doi.org/10.1117/12.2254358
Event: SPIE OPTO, 2017, San Francisco, California, United States

Abstract

Early detection of diseases can save lives. Hence, there is emphasis in sorting rare disease-indicating cells within small dilute quantities such as in the confines of lab-on-a-chip devices. However, before diseased cells can be studied in isolation, it is necessary to identify them against normal healthy cells. With the richness of visual information, a lot of microscopy techniques have been developed and have been crucial in biological studies. To utilize their complementary advantages we adopt both fluorescence and brightfield imaging in our optical cell sorter. Brightfield imaging has the advantage of being non-invasive, thus maintaining cell viability. Fluorescence imaging, on the other hand, takes advantages of the chemical specificity of fluorescence markers and can validate machine vision results from brightfield images. Visually identified cells are sorted using optical manipulation techniques. Scattering forces from beams actuated via efficient phase-only efficient modulation has been adopted. This has lowered the required power for sorting cells to a tenth of our previous approach, and also makes the cell sorter safer for use in clinical settings. With the versatility of dynamically programmable phase spatial light modulators, a plurality of light shaping techniques, including hybrid approaches, can be utilized in cell sorting.

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Andrew Bañas, Caro Carrissemoux, Mark Villangca, Darwin Palima, and Jesper Glückstad "Optical cell sorting with multiple imaging modalities", Proc. SPIE 10120, Complex Light and Optical Forces XI, 1012018 (27 February 2017); https://doi.org/10.1117/12.2254358

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KEYWORDS

Machine vision

Cameras

Microscopy

Image processing

Microfluidics

Visualization

Information visualization

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