Quantitative phase microscopy (QPM) techniques developed so far primarily belongs to high speed transmitted light based systems that has enough sensitivity to resolve membrane fluctuations and dynamics, but has no depth resolution. Therefore, most biomechanics studies using QPM today is confined to simple cells, such as RBCs, without internal organelles. An important instrument that will greatly extend the biomedical applications of QPM is to develop next generation microscope with 3D capability and sufficient temporal resolution to study biomechanics of complex eukaryotic cells including the mechanics of their internal compartments. For eukaryotic cells, the depth sectioning capability is critical and should be sufficient to distinguish nucleic membrane fluctuations from plasma membrane fluctuations. Further, this microscope must provide high temporal resolution since typical eukaryotes membranes are substantially stiffer than RBCs. A confocal reflectance quantitative phase microscope is presented based on multi-pinhole scanning, with the capabilities of higher temporal resolution and sensitivity for nucleic and plasma membranes of eukaryotic cells. System hardware is developed based on an array of confocal pinhole generated by using the ‘ON’ state of subset of micro-mirrors of digital micro-mirror device (DMD, from Texas Instruments) and high-speed raster scanning provides 14ms imaging speed in wide-field mode. A common path interferometer is integrated at the imaging arm for detection of specimens’ quantitative phase information. Theoretical investigation of quantitative phase reconstructed from system is investigated and application of system is presented for dimensional fluctuations measurements of both cellular plasma and nucleic membranes of embryonic stem cells.
Vijay Raj Singh, Zahid Yaqoob, and Peter T. C. So, "Confocal reflectance quantitative phase microscope system for cellular membranes dynamics study (Conference Presentation)," Proc. SPIE 10074, Quantitative Phase Imaging III, 100740I (Presented at SPIE BiOS: January 30, 2017; Published: 24 April 2017); https://doi.org/10.1117/12.2252350.5380600128001.
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