Efficient parallel implementation of iterative reconstruction algorithms for electron tomography

José Jesús Fernández, Dan Gordon, Rachel Gordon

Research output: Contribution to journalArticlepeer-review


Electron tomography (ET) combines electron microscopy and the principles of tomographic imaging in order to reconstruct the three-dimensional structure of complex biological specimens at molecular resolution. Weighted back-projection (WBP) has long been the method of choice since the reconstructions are very fast. It is well known that iterative methods produce better images, but at a very costly time penalty. In this work, it is shown that efficient parallel implementations of iterative methods, based primarily on data decomposition, can speed up such methods to an extent that they become viable alternatives to WBP. Precomputation of the coefficient matrix has also turned out to be important to substantially improve the performance regardless of the number of processors used. Matrix precomputation has made it possible to speed up the block-iterative component averaging (BICAV) algorithm, which has been studied before in the context of computerized tomography (CT) and ET, by a factor of more than 3.7. Component-averaged row projections (CARP) is a recently introduced block-parallel algorithm, which was shown to be a robust method for solving sparse systems arising from partial differential equations. It is shown that this algorithm is also suitable for single-axis ET, and is advantageous over BICAV both in terms of runtime and image quality. The experiments were carried out on several datasets of ET of various sizes, using the blob model for representing the reconstructed object.

Original languageEnglish
Pages (from-to)626-640
Number of pages15
JournalJournal of Parallel and Distributed Computing
Issue number5
StatePublished - May 2008

Bibliographical note

Funding Information:
Thanks are due to the Biocomputing Unit (BCU) of the Centro Nacional de Biotecnología (CNB), Madrid, Spain, for supporting the visit of the second and third authors in October 2005, when this research was initiated. Special thanks are due to Prof José-María Carazo, head of the BCU, and the staff of BCU, for many instructive discussions. The authors also wish to thank Dr J.L. Carrascosa and Dr G. Perkins for kindly providing the datasets from the Vaccinia virus and mitochondrion, respectively. This work has been partially supported by the Spanish MEC (Grant TIN2005-00447), Junta de Andalucia (Grant P06-TIC-01426) and EU (Contract LSHG-CT-2004-502828). The authors are indebted to the anonymous reviewers whose many detailed comments have helped to improve the presentation of our results.


  • CARP
  • CAV
  • Component-averaging
  • Electron microscopy
  • Electron tomography
  • Image reconstruction
  • Parallel processing
  • WBP
  • Weighted back-projection

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computer Networks and Communications
  • Artificial Intelligence


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