ArticleBMC bioinformatics2020
Compressed sensing improved iterative reconstruction-reprojection algorithm for electron tomography.
Article in BMC bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- An intelligent workflow for sub-nanoscale 3D reconstruction of intact synapses from serial section electron tomography.BMC biology · 2023Article
- Automatic synchrotron tomographic alignment schemes based on genetic algorithms and human-in-the-loop software.Journal of synchrotron radiation · 2023Article
- Compressed sensing for electron cryotomography and high-resolution subtomogram averaging of biological specimens.Structure (London, England : 1993) · 2022Article
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Authors and funding
6 authors.
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Abstract
backgroundElectron tomography (ET) is an important technique for the study of complex biological structures and their functions. Electron tomography reconstructs the interior of a three-dimensional object from its projections at different orientations. However, due to the instrument limitation, the angular tilt range of the projections is limited within +70
resultsIn this paper, we proposed a novel algorithm, compressed sensing improved iterative reconstruction-reprojection (CSIIRR), which follows the schedule of improved iterative reconstruction-reprojection but further considers the sparsity of the biological ultra-structural content in specimen. The proposed algorithm keeps both the merits of the improved iterative reconstruction-reprojection (IIRR) and compressed sensing, resulting in an estimation of the electron tomography with faster execution speed and better reconstruction result. A comprehensive experiment has been carried out, in which CSIIRR was challenged on both simulated and real-world datasets as well as compared with a number of classical methods. The experimental results prove the effectiveness and efficiency of CSIIRR, and further show its advantages over the other methods.
conclusionsThe proposed algorithm has an obvious advance in the suppression of missing wedge effects and the restoration of missing information, which provides an option to the structural biologist for clear and accurate tomographic reconstruction.
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