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Proceedings Paper

Statistically optimal image reconstruction for multi-detector intensity diffraction tomography
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Paper Abstract

Intensity diffraction tomography (I-DT) is an in-line holographic imaging method for reconstructing the three-dimensional complex refractive index distribution of a weakly scattering object. Because it circumvents the phase retrieval problem of diffraction tomography, I-DT reconstruction methods may benefit a range of imaging problems involving optical and coherent X-ray radiation. In this work, we investigate the use of statistically complementary data, provided by multiple (> 2) in-line intensity measurements, for effective suppression of image noise in I-DT. The noise properties of the reconstructed images are demonstrated to depend strongly on the specification of measurement geometry. The effects of experimental uncertainties on the performance of I-DT is investigated also. Computer-simulation studies that are representative of a tomographic microscopy implementation of I-DT are presented.

Paper Details

Date Published: 5 September 2006
PDF: 11 pages
Proc. SPIE 6316, Image Reconstruction from Incomplete Data IV, 63160K (5 September 2006); doi: 10.1117/12.682987
Show Author Affiliations
Yin Huang, Illinois Institute of Technology (United States)
Mark A. Anastasio, Illinois Institute of Technology (United States)


Published in SPIE Proceedings Vol. 6316:
Image Reconstruction from Incomplete Data IV
Philip J. Bones; Michael A. Fiddy; Rick P. Millane, Editor(s)

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