20 February 2018 Multi-channel imaging cytometry with a single detector
Author Affiliations +
Multi-channel microscopy and multi-channel flow cytometry generate high bit data streams. Multiple channels (both spectral and spatial) are important in diagnosing diseased tissue and identifying individual cells. Omega Optical has developed techniques for mapping multiple channels into the time domain for detection by a single high gain, high bandwidth detector. This approach is based on pulsed laser excitation and a serial array of optical fibers coated with spectral reflectors such that up to 15 wavelength bins are sequentially detected by a single-element detector within 2.5 μs. Our multichannel microscopy system uses firmware running on dedicated DSP and FPGA chips to synchronize the laser, scanning mirrors, and sampling clock. The signals are digitized by an NI board into 14 bits at 60MHz – allowing for 232 by 174 pixel fields in up to 15 channels with 10x over sampling. Our multi-channel imaging cytometry design adds channels for forward scattering and back scattering to the fluorescence spectral channels. All channels are detected within the 2.5 μs – which is compatible with fast cytometry. Going forward, we plan to digitize at 16 bits with an A-toD chip attached to a custom board. Processing these digital signals in custom firmware would allow an on-board graphics processing unit to display imaging flow cytometry data over configurable scanning line lengths. The scatter channels can be used to trigger data buffering when a cell is present in the beam. This approach enables a low cost mechanically robust imaging cytometer.
Conference Presentation
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sarah Locknar, Sarah Locknar, John Barton, John Barton, Mark Entwistle, Mark Entwistle, Gary Carver, Gary Carver, Robert Johnson, Robert Johnson, } "Multi-channel imaging cytometry with a single detector", Proc. SPIE 10505, High-Speed Biomedical Imaging and Spectroscopy III: Toward Big Data Instrumentation and Management, 105050G (20 February 2018); doi: 10.1117/12.2290773; https://doi.org/10.1117/12.2290773

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