AI Chat Paper
Discover the SciOpen Platform and Achieve Your Research Goals with Ease.
Electron tomography (ET) plays an important role in studying in situ cell ultrastructure in three-dimensional space. Due to limited tilt angles, ET reconstruction always suffers from the “missing wedge” problem. With a validation procedure, iterative compressed-sensing optimized NUFFT reconstruction (ICON) demonstrates its power in the restoration of validated missing information for low SNR biological ET dataset. However, the huge computational demand has become a major problem for the application of ICON. In this work, we analyzed the framework of ICON and classified the operations of major steps of ICON reconstruction into three types. Accordingly, we designed parallel strategies and implemented them on graphics processing units (GPU) to generate a parallel program ICON-GPU. With high accuracy, ICON-GPU has a great acceleration compared to its CPU version, up to 83.7×, greatly relieving ICON’s dependence on computing resource.
Batenburg K, Sijbers J, (2011) Dart: a practical reconstruction algorithm for discrete tomography.IEEE Trans Image Process 20(9):2542
Carazo JM, Carrascosa JL, (1987) Restoration of direct Fourier three-dimensional reconstructions of crystalline specimens by the method of convex projections.J Microsc 145(Pt 2):159-177
Castaño-Díez D, Kudryashev M, Arheit M, Stahlberg H, (2012) Dynamo : a flexible, user-friendly development tool for subtomogram averaging of cryo-em data in high-performance computing environments.J Struct Biol 178(2):139
Chen Y, Förster F, (2014) Iterative reconstruction of cryo-electron tomograms using nonuniform fast Fourier transforms.J Struct Biol 185(3):309-316
Chen Y, Zhang Y, Zhang K, Deng Y, Wang S, Zhang F, Sun F, (2016) Firt: filtered iterative reconstruction technique with information restoration.J Struct Biol 195(1):49-61
Deng Y, Chen Y, Zhang Y, Wang S, Zhang F, Sun F, (2016) Icon: 3d reconstruction with ‘missing-information’ restoration in biological electron tomography.J Struct Biol 195(1):100
Donoho DL, (2006) Compressed sensing.IEEE Trans Inf Theory 52(4):1289-1306
Fernández JJ, (2008) High performance computing in structural determination by electron cryomicroscopy.J Struct Biol 164(1):1-6
Fernández JJ, Carazo JM, García I, (2004) Three-dimensional reconstruction of cellular structures by electron microscope tomography and parallel computing.J Parallel Distrib Comput 64(2):285-300
Fridman K, Mader A, Zwerger M, Elia N, Medalia O, (2012) Advances in tomography: probing the molecular architecture of cells.Nat Rev Mol Cell Biol 13(13):736-742
Gilbert P, (1972) Iterative methods for the three-dimensional reconstruction of an object from projections.J Theor Biol 36(1):105-117
Goldstein AA, (1965) On steepest descent.J Soc Ind Appl Math 3(1):147-151
Goris B, Broek WVD, Batenburg KJ, Mezerji HH, Bals S, (2012) Electron tomography based on a total variation minimization reconstruction technique.Ultramicroscopy 113(1):120-130
Han R, Zhang F, Wan X, Fernández JJ, Sun F, Liu Z, (2014) A marker-free automatic alignment method based on scale-invariant features.J Struct Biol 186(1):167-180
Keiner J, Kunis S, Potts D, (2010) Using NFFT 3—a software library for various nonequispaced fast Fourier transforms.ACM Trans Math Softw 36(4):1-30
Leary R, Saghi Z, Holland PAMDJ, (2013) Compressed sensing electron tomography: theory and applications.Ultramicroscopy 131(8):70-91
Liao X, Xiao L, Yang C, Lu Y, (2014) Milkyway-2 supercomputer: system and application.Front Comput Sci 8(3):345-356
Lindholm E, Nickolls J, Oberman S, Montrym J, (2008) NVIDIA tesla: a unified graphics and computing architecture.IEEE Micro 28(2):39-55
Lučić V, Förster F, Baumeister W, (2005) Structural studies by electron tomography: from cells to molecules.Annu Rev Biochem 74(1):833
Lučić V, Rigort A, Baumeister W, (2013) Cryo-electron tomography: the challenge of doing structural biology in situ.J Cell Biol 202(3):407-419
Mersereau RM, (1976) Direct Fourier transform techniques in 3-d image reconstruction.Comput Biol Med 6(4):247
Rigort A, Villa E, Bäuerlein FJB, Engel BD, Plitzko JM, (2012) Chapter 14—integrative approaches for cellular cryo-electron tomography: correlative imaging and focused ion beam micromachining.Methods Cell Biol 111:259-281
Saghi Z, Holland DJ, Leary R, Falqui A, Bertoni G, Sederman AJ, Gladden LF, Midgley PA, (2011) Three-dimensional morphology of iron oxide nanoparticles with reactive concave surfaces. A compressed sensing-electron tomography (CS-ET) approach.Nano Lett 11(11):4666-4673
Saghi Z, Divitini G, Winter B, Leary R, Spiecker E, Ducati C, Midgley PA, (2015) Compressed sensing electron tomography of needle-shaped biological specimens—potential for improved reconstruction fidelity with reduced dose.Ultramicroscopy 160:230-238
Sezan MI, Stark H, (1983) Image restoration by convex projections in the presence of noise.Appl Opt 22(18):2781
Yahav T, Maimon T, Grossman E, Dahan I, Medalia O, (2011) Cryo-electron tomography: gaining insight into cellular processes by structural approaches.Curr Opin Struct Biol 21(5):670-677
Yang SC, Wang YL, Jiao GS, Qian HJ, Lu ZY, (2015) Accelerating electrostatic interaction calculations with graphical processing units based on new developments of ewald method using non-uniform fast Fourier transform.J Comput Chem 37(3):378
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
