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A computational study of reconstruction algorithms for diffraction tomography: Interpolation versus filtered-backpropagation
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Image ReconstructionEngineeringMicroscopySparse ImagingSignal ReconstructionComputational ImagingDance ImagesDiffraction TomographyRadiologyHealth SciencesReconstruction TechniqueMedical ImagingDiffractionInverse ProblemsDeconvolutionMedical Image ComputingComputational Optical ImagingTutorial PartPhase RetrievalComputational StudyReconstruction AlgorithmsBiomedical ImagingTutorial IntroductionImage RestorationTomography
From the standpoint of reporting a new contribution, this paper shows that by using bilinear interpolation followed by direct two-dimensional Fourier inversion, one can obtain reconstructions of quality which is comparable to that produced by the filtered-backpropagation algorithm proposed recently by Devaney. For an N × N image reconstructed from N diffracted projections, the former approach requires approximately 4N FFT's, whereas the backpropagation technique requires approximately N <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> FFT's. We have also taken this opportunity to present the reader with a tutorial introduction to diffraction tomography, an area that is becoming increasingly important not only in medical imaging, but also in underwater and seismic mapping with microwaves and sound. The main feature of the tutorial part is the statement of the Fourier diffraction projection theorem, which is an extension of the traditional Fourier slice theorem to the case of image formation with diffracting illumination.
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