Three-Dimensional Image Reconstruction From Planar Projections With Application To Optical Data Processing

Harrison H. Barrett

doi:10.1117/12.934547

27 February 1984 Three-Dimensional Image Reconstruction From Planar Projections With Application To Optical Data Processing

Harrison H. Barrett

Author Affiliations +

Proceedings Volume 0373, Transformations in Optical Signal Processing; (1984) https://doi.org/10.1117/12.934547
Event: Transformations in Optical Signal Processing, 1981, Seattle, United States

Abstract

Abstract. The term planar projection refers to the integral of a three-dimensional (3-D) function over a plane, as opposed to the line integrals that form the basic data set of computed tomography. Planar projections arise naturally in nuclear imaging when a slit aperture is used, in imaging with nuclear spin resonance, and in time-domain scattering studies. If an appropriate set of translations and rotations of the plane of integration is carried out, a complete data set is generated and a reconstruction of the 3-D object is possible. Various reconstruction algorithms are discussed and compared to the more familiar case of computed tomography. Another potential application of planar projections is in general 3-D data processing, where it should be useful to preprocess the data by generating a set of planar integrals, even if the original data have nothing to do with projections. This has the effect of reducing 3-D operations such as convolutions and correlations to one-dimensional (1-D) operations, which are more readily performed. After a subsequent reconstruction from the filtered projections, the final 3-D result is equivalent to that which would have been obtained by 3-D operations. Several incoherent optical systems for performing the projection and reconstruction operations are described.

Citation Download Citation

Harrison H. Barrett "Three-Dimensional Image Reconstruction From Planar Projections With Application To Optical Data Processing", Proc. SPIE 0373, Transformations in Optical Signal Processing, (27 February 1984); https://doi.org/10.1117/12.934547

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