Identification of fluorescent beads using a coded aperture snapshot spectral imager.
Abstract
We apply a coded aperture snapshot spectral imager (CASSI) to fluorescence microscopy.
CASSI records a two-dimensional (2D) spectrally filtered projection of a three-dimensional
(3D) spectral data cube. We minimize a convex quadratic function with total variation
(TV) constraints for data cube estimation from the 2D snapshot. We adapt the TV minimization
algorithm for direct fluorescent bead identification from CASSI measurements by combining
a priori knowledge of the spectra associated with each bead type. Our proposed method
creates a 2D bead identity image. Simulated fluorescence CASSI measurements are used
to evaluate the behavior of the algorithm. We also record real CASSI measurements
of a ten bead type fluorescence scene and create a 2D bead identity map. A baseline
image from filtered-array imaging system verifies CASSI's 2D bead identity map.
Type
Journal articleSubject
AlgorithmsFluorescent Dyes
Imaging, Three-Dimensional
Microspheres
Optical Devices
Optical Phenomena
Spectrometry, Fluorescence
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https://hdl.handle.net/10161/4204Collections
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Show full item recordScholars@Duke
David J. Brady
Michael J. Fitzpatrick Distinguished Professor Emeritus of Photonics
David Brady leads the Duke Information Spaces Project (DISP). Historically, DISP has
focused on computational imaging systems, with particular emphasis on smart cameras
for security, consumer, transportation and broadcast applications. Currently DISP
focuses primarily on the use of artificial intelligence in camera arrays for interactive
broadcasting.

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