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GENFIRE: A generalized Fourier iterative reconstruction algorithm for high-resolution 3D imaging.

  • Author(s): Pryor, Alan
  • Yang, Yongsoo
  • Rana, Arjun
  • Gallagher-Jones, Marcus
  • Zhou, Jihan
  • Lo, Yuan Hung
  • Melinte, Georgian
  • Chiu, Wah
  • Rodriguez, Jose A
  • Miao, Jianwei
  • et al.
Abstract

Tomography has made a radical impact on diverse fields ranging from the study of 3D atomic arrangements in matter to the study of human health in medicine. Despite its very diverse applications, the core of tomography remains the same, that is, a mathematical method must be implemented to reconstruct the 3D structure of an object from a number of 2D projections. Here, we present the mathematical implementation of a tomographic algorithm, termed GENeralized Fourier Iterative REconstruction (GENFIRE), for high-resolution 3D reconstruction from a limited number of 2D projections. GENFIRE first assembles a 3D Fourier grid with oversampling and then iterates between real and reciprocal space to search for a global solution that is concurrently consistent with the measured data and general physical constraints. The algorithm requires minimal human intervention and also incorporates angular refinement to reduce the tilt angle error. We demonstrate that GENFIRE can produce superior results relative to several other popular tomographic reconstruction techniques through numerical simulations and by experimentally reconstructing the 3D structure of a porous material and a frozen-hydrated marine cyanobacterium. Equipped with a graphical user interface, GENFIRE is freely available from our website and is expected to find broad applications across different disciplines.

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