Paper
3 April 1995 Increased photon-counting efficiency for multispectral imaging using rotational spectrotomography
Paul A. Bernhardt
Author Affiliations +
Abstract
Multi-spectral imaging can be powerful tool for medical diagnostics. Many time resolved or low-light-level applications require large photon throughput to distinguish between areas of normal and diseased tissues. The throughput of a dispersive, imaging spectrometer is often much less than unity and consequently limits sensitivity. Common multi-spectral approaches use either (1) narrow band filters to isolate 2D spatial images for each spectral wavelength channel or (2) a slit spectrograph to image one spatial and one spectral dimension as the slit is scanned across the object. Both of these approaches are inefficient because photons outside the filter passband or the slit area are not detected. A new imaging technique called spectro- tomography collects all available photons and employs computer tomography to reconstruct the 3D data cube of the image. A rotational spectro-tomographic imager has been designed with a circular aperture, objective-grating camera that is rotated in steps around its optical axis. A sequence of images is obtained with fixed steps in camera angle by rotation and lens focal-length by zooming. These images provide a sufficient number of 2D projections of the 3D data cube for accurate reconstruction. Both direct Fourier transform and filter- backprojection algorithms have been developed for tomographic reconstructions. The data cube of a broad spectrum object with 64 spectral bands and 64 X 64 spatial resolution elements has been used as the test case for a numerical example of the technique.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Paul A. Bernhardt "Increased photon-counting efficiency for multispectral imaging using rotational spectrotomography", Proc. SPIE 2386, Ultrasensitive Instrumentation for DNA Sequencing and Biochemical Diagnostics, (3 April 1995); https://doi.org/10.1117/12.206030
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KEYWORDS
Imaging systems

Sensors

Fourier transforms

3D image processing

Cameras

Optical filters

Image filtering

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