1. Articles from Alex S. Reinstein

    1-2 of 2
    1. Depth-encoded spectral domain phase microscopy for simultaneous multi-site nanoscale optical measurements

      Depth-encoded spectral domain phase microscopy for simultaneous multi-site nanoscale optical measurements
      Spectral domain phase microscopy (SDPM) is an extension of spectral domain optical coherence tomography (SDOCT) that exploits the extraordinary phase stability of spectrometer-based systems with common-path geometry to resolve sub-wavelength displacements within a sample volume. This technique has been implemented for high resolution axial displacement and velocity measurements in biological samples, but since axial displacement information is acquired serially along the lateral dimension, it has been unable to measure fast temporal dynamics in extended samples. Depth-encoded SDPM (DESDPM) uses multiple sample arms with unevenly spaced common path reference reflectors to multiplex independent SDPM signals from separate lateral positions on a ...
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      Mentions: Duke University
    2. Depth-encoded spectral domain phase microscopy for simultaneous multisite nanoscale optical measurements of nerve activation

      Spectral Domain Phase Microscopy (SDPM) is a recent extension of Spectral Domain Optical Coherence Tomography (SDOCT) that exploits the extraordinary phase stability of spectrometer-based systems with common-path geometry to resolve sub-wavelength displacements within a sample volume. This technique has been implemented for high resolution axial displacement and velocity measurements in biological samples, but since axial displacement information is acquired serially, has been unable to measure fast temporal dynamics in extended samples. Depth-Encoded SDPM (DESDPM) uses multiple sample arms with unevenly spaced common path reference reflectors to multiplex independent SDPM signals from separate lateral positions on a sample simultaneously using a ...
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      Mentions: Duke University
    1-2 of 2
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    1. (2 articles) Duke University
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