3DEM-Methods - User contributions [en]

Main Page

2011-07-29T20:52:47Z

Jjfdez: /* People developing methods */

This web page is intended to be an extensive repository of three-dimensional electron microscopy (3DEM) methods. The advantages of having such a repository are

* You know which are the relevant articles in a particular topic, therefore, paper introductions, reviews, etc. are easier to write and you make sure you will cite all the related articles.
* You will be sure that your paper has more chances of being cited.
* You can add whatever information you find relevant to your method, external links, links to other papers, etc.
* You can link your method to a web page providing the corresponding software, so you know people can use your algorithms.
* You can use the Wiki search capabilities to locate relevant articles even if they are not at the topic you are looking at.
* As a community we will "reconstruct" our history.

Developing image processing methods for 3DEM is not "[[well-paid]]" in terms of citations and impact factor. However, it is crucial for the advance of the field. Gathering methodological papers in a portal will help to increase the recognition of the field.

Please:

* Add your articles at the right place (you can add a single article in several topics if it is relevant to all of them). The easiest way to add an article is by editing the corresponding topic in the main page, adding your entry, then save the main page. Click on the red link that appears on your new entry, copy and paste the Wiki following code, add the information of your article

== Citation ==

== Abstract ==

== Keywords ==

== Links ==

== Related software ==

== Related methods ==

== Comments ==

* Maintain the information of each article as complete as possible.
* Sort articles by years and authors.
* Be respectful to other people's work.

== Electron microscopy images ==

=== Image formation ===

{|

| Paper
| [[1971Glaeser_Damage]]
| Radiation damage
|-

| Paper
| [[1975Unwin_Imaging]]
| Radiation dose
|-

| Paper
| [[1988Toyoshima_Model]]
| Amplitud constrast
|-

| Paper
| [[1993Toyoshima_Model]]
| Amplitud constrast
|-

| Paper
| [[2002DeCarlo_Damage]]
| Radiation damage in cryonegative staining
|-

| Paper
| [[2004Egerton_Damage]]
| Radiation damage
|-

| Paper
| [[2004Sorzano_Normalization]]
| Background noise is Gaussian
|-

| Paper
| [[2008Fanelli_ImageFormation]]
| Review on the image formation model from the electron waves and open inverse-problems
|-

| Paper
| [[2010Zewail_FourDimensional]]
| Review on the use of ultrafast EM
|-

|}

=== Collection geometry ===

{|

| Chapter
| [[1980Hoppe_Wedge]]
| Missing wedge
|-

| Paper
| [[1988Radermacher_RCT]]
| Random Conical Tilt and Single axis tilt
|-

| Paper
| [[1995Penczek_Dual]]
| Dual axis tomography
|-

| Paper
| [[1997Mastronarde_Dual]]
| Dual axis tomography
|-

| Paper
| [[2005Lanzavecchia_Conical]]
| Conical tomography
|-

| Paper
| [[2005Zampighi_Conical]]
| Conical tomography
|-

| Paper
| [[2006Leschziner_OT]]
| Orthogonal Tilt
|-

| Paper
| [[2006Messaoudi_Multiple]]
| Multiple axis tomography
|-

|}

=== Sample preparation ===

{|

| Paper
| [[1982Dubochet_Sample]]
| Vitreous ice
|-

| Paper
| [[1986Lepault_Sample]]
| Fast freezing
|-

| Paper
| [[1995Dubochet_Sample]]
| High-pressure freezing
|-

| Paper
| [[1995VanMarle_Sample]]
| Sample damages in resin
|-

| Paper
| [[1998Adrian_Sample]]
| Cryo negative staining
|-

| Paper
| [[2002DeCarlo_Damage]]
| Radiation damage in cryonegative staining
|-

| Paper
| [[2002Hsieh_Sample]]
| Cryofixation
|-

| Paper
| [[2004AlAmoudi_Sample]]
| CEMOVIS
|-

| Paper
| [[2008Studer_Sample]]
| Review on high pressure freezing
|-

| Paper
| [[2009Pierson_Sample]]
| Review on sample preparation for electron tomography
|-

|}

=== Automated data collection ===

{|

| Paper
| [[1992Dierksen_Automatic]]
| Automated data collection
|-

| Paper
| [[1992Koster_Automatic]]
| Automated data collection
|-

| Paper
| [[2001Zhang_Automatic]]
| Automated sample collection
|-

| Paper
| [[2003Ziese_Automatic]]
| Automated autofocusing
|-

| Paper
| [[2004Potter_Automatic]]
| Automated sample loading
|-

| Paper
| [[2004Zheng_Automatic]]
| Automated data collection
|-

| Paper
| [[2005Lei_Automatic]]
| Automated data collection: AutoEM
|-

| Paper
| [[2005Suloway_Automatic]]
| Automated data collection: Leginon
|-

|}

== Single particles ==

=== Automatic particle picking ===

{|

| Paper
| [[1982VanHeel_Detection]]
| Detection of particles in micrographs
|-

| Paper
| [[2001Nicholson_Review]]
| Review on automatic particle picking
|-

| Paper
| [[2001Zhu_Filaments]]
| Automatic identification of filaments in micrographs
|-

| Paper
| [[2004Zhu_Review]]
| Review on automatic particle picking
|-

| Paper
| [[2009Sorzano_MachineLearning]]
| Automatic particle picking based on machine learning of rotational invariants
|-

|}

=== 2D Preprocessing ===

{|

| Paper
| [[2003Rosenthal_DPR]]
| Contrast enhancement through DPR
|-

| Paper
| [[2004Sorzano_Normalization]]
| Normalization procedures and their statistical properties.
|-

| Paper
| [[2006Sorzano_Denoising]]
| Strong denoising in wavelet space
|-

| Conference
| [[2009Sorzano_Downsampling]]
| Differences between the different downsampling schemes
|-

|}

=== 2D Alignment ===

{|

| Paper
| [[1981Frank_Averaging]]
| 2D averaging and phase residual
|-

| Paper
| [[1982Saxton_Averaging]]
| 2D averaging using correlation
|-

| Paper
| [[1998Sigworth_ML2D]]
| Maximum likelihood alignment in 2D
|-

| Paper
| [[2005Scheres_ML2D]]
| Multireference alignment and classification in 2D
|-

| Paper
| [[2010Sorzano_CL2D]]
| Multireference alignment and classification in 2D
|-

|}

=== 2D Classification and clustering ===

{|

| Paper
| [[1981VanHeel_MSA]]
| Multivariate Statistical Analysis
|-

| Paper
| [[1984VanHeel_MSA]]
| Multivariate Statistical Analysis
|-

| Paper
| [[2005Scheres_ML2D]]
| Multireference alignment and classification in 2D
|-

| Paper
| [[2010Sorzano_CL2D]]
| Multireference alignment and classification in 2D
|-

|}

=== 3D Alignment ===

{|

| Paper
| [[1987VanHeel_CommonLines]]
| Angular assignment using common lines (reference free)
|-

| Paper
| [[1988Provencher_Simultaneous]]
| Simultaneaous alignment and reconstruction
|-

| Paper
| [[1988Radermacher_RCT]]
| Random Conical Tilt and Single axis tilt
|-

| Paper
| [[1988Vogel_Simultaneous]]
| Simultaneaous alignment and reconstruction
|-

| Paper
| [[1990Gelfand_Moments]]
| Angular assignment using moments (reference free)
|-

| Paper
| [[1990Goncharov_Moments]]
| Angular assignment using moments (reference free)
|-

| Paper
| [[1994Penczek_Real]]
| Angular assignment using projection matching in real space
|-

| Paper
| [[1994Radermacher_Radon]]
| Angular assignment in Radon space
|-

| Paper
| [[1996Penczek_CommonLines]]
| Angular assignment using common lines (reference free)
|-

| Paper
| [[2003Rosenthal_DPR]]
| Angular assignment using DPR
|-

| Paper
| [[2004Sorzano_Wavelet]]
| Angular assignment in the wavelet space.
|-

| Paper
| [[2005Jonic_Splines]]
| Angular assignment in Fourier space using spline interpolation.
|-

| Paper
| [[2005Yang_Simultaneous]]
| Simultaneaous alignment and reconstruction
|-

| Paper
| [[2007Grigorieff_Continuous]]
| Continuous angular assignment in Fourier space
|-

|}

=== 3D Reconstruction ===
{|

| Paper
| [[1972Gilbert_SIRT]]
| Simultaneous Iterative Reconstruction Technique (SIRT)
|-

| Paper
| [[1973Herman_ART]]
| Algebraic Reconstruction Technique (ART)
|-

| Paper
| [[1984Andersen_SART]]
| Simultaneous Algebraic Reconstruction Technique (SART)
|-

| Paper
| [[1986Harauz_FBP]]
| Exact filters for Filtered Back Projection
|-

| Chapter
| [[1992Radermacher_WBP]]
| Exact filters for Weighted Back Projection
|-

| Paper
| [[1997Zhu_RecCTF]]
| 3D Reconstruction (SIRT like) and simultaneous CTF correction
|-

| Paper
| [[1998Boisset_Uneven]]
| Artifacts in SIRT and WBP under uneven angular distributions
|-

| Paper
| [[1998Marabini_ART]]
| Algebraic Reconstruction Technique with blobs (Xmipp)
|-

| Paper
| [[2001Sorzano_Uneven]]
| Free parameter selection under uneven angular distributions
|-

| Paper
| [[2005Sorzano_Parameters]]
| Free parameter selection for optimizing multiple tasks
|-

| Paper
| [[2008Sorzano_Constraints]]
| Mass, surface, positivity and symmetry constraints for real-space algorithms
|-

| Paper
| [[2009Bilbao_ParallelART]]
| Efficient parallelization of ART
|-

|}

=== 3D Heterogeneity ===

{|

| Paper
| [[2004White_Size]]
| Heterogeneity classification of differently sized images
|-

| Paper
| [[2007Leschziner_Review]]
| Review of 3D heterogeneity handling algorithms
|-

| Paper
| [[2007Scheres_ML3D]]
| Maximum Likelihood alignment and classification in 3D
|-

|}

=== Resolution ===

{|

| Paper
| [[1986Harauz_FBP]]
| Fourier Shell Correlation
|-

| Paper
| [[1987Unser_SSNR]]
| 2D Spectral Signal to Noise Ratio
|-

| Paper
| [[2002Penczek_SSNR]]
| 3D Spectral Signal to Noise Ratio for Fourier based algorithms
|-

| Paper
| [[2003Rosenthal_DPR]]
| Review of the FSC and establishment of a new threshold
|-

| Paper
| [[2005Unser_SSNR]]
| 3D Spectral Signal to Noise Ratio for any kind of algorithms
|-

| Paper
| [[2005VanHeel_FSC]]
| Establishment of a new threshold for FSC
|-

| Paper
| [[2007Sousa_AbInitio]]
| Resolution measurement on neighbour Fourier voxels
|-

|}

=== Sharpening of high resolution information ===
{|

| Paper
| [[2003Rosenthal_DPR]]
| Contrast restoration and map sharpening
|-

| Paper
| [[2008Fernandez_Bfactor]]
| Bfactor determination and restoration
|-

|}

=== CTF estimation and restoration ===

{|

| Paper
| [[1971Thon_Model]]
| CTF model
|-

| Paper
| [[1984Cohen_Validity]]
| Validity of the CTF model at high frequencies
|-

| Paper
| [[1988Toyoshima_Model]]
| CTF estimation
|-

| Paper
| [[1993Toyoshima_Model]]
| Amplitud constrast
|-

| Paper
| [[1995Frank_Wiener]]
| CTF correction using Wiener filter
|-

| Paper
| [[1996Skoglund_MaxEnt]]
| CTF correction with Maximum Entropy
|-

| Paper
| [[1996Zhou_Model]]
| CTF model and user interface for manual fitting
|-

| Paper
| [[1997Fernandez_AR]]
| PSD estimation using periodogram averaging and AR models
|-

| Paper
| [[1997Penczek_Wiener]]
| CTF correction using Wiener filter
|-

| Paper
| [[1997Stark_Deconvolution]]
| CTF correction using deconvolution
|-

| Paper
| [[1997Zhu_RecCTF]]
| CTF correction and reconstruction
|-

| Paper
| [[2000DeRosier_EwaldCorrection]]
| CTF correction considering the Ewald sphere
|-

| Paper
| [[2000Jensen_TiltedCorrection]]
| CTF correction considering tilt in backprojection
|-

| Paper
| [[2001Saad_CTFEstimate]]
| CTF estimation
|-

| Paper
| [[2003Huang_CTFEstimate]]
| CTF estimation
|-

| Paper
| [[2003Mindell_CTFTILT]]
| CTF estimation for tilted micrographs
|-

| Paper
| [[2003Velazquez_ARMA]]
| PSD and CTF estimation using ARMA models
|-

| Paper
| [[2004Sorzano_IDR]]
| CTF restoration and reconstruction with Iterative Data Refinement
|-

| Paper
| [[2004Zubelli_Chahine]]
| CTF restoration and reconstruction with Chahine's multiplicative method
|-

| Conference
| [[2005Dubowy_SpaceVariant]]
| CTF correction when this is space variant
|-

| Paper
| [[2005Mallick_ACE]]
| CTF estimation
|-

| Paper
| [[2006Wolf_Ewald]]
| CTF correction considering Ewald sphere
|-

| Paper
| [[2007Jonic_EnhancedPSD]]
| PSD enhancement for better identification of Thon rings; Vitreous ice diffracts in Thon rings
|-

| Paper
| [[2007Philippsen_Model]]
| CTF Model for tilted specimens
|-

| Paper
| [[2007Sorzano_CTF]]
| CTF estimation using enhanced PSDs
|-

| Paper
| [[2009Sorzano_Sensitivity]]
| Error sensitivity of the CTF models, non-uniqueness of the CTF parameters
|-

|}

=== Segmentation ===

{|

| Paper
| [[2006Baker_segmentation]]
| Segmentation of molecular subunits
|-

|}

=== Fitting and docking ===

{|

| Paper
| [[1999Volkmann_Fitting]]
| Fitting in real space
|-

| Paper
| [[2001Baker_Review]]
| Review of protein structure prediction
|-

| Paper
| [[2001Jones_Review]]
| Review of protein structure prediction
|-

| Paper
| [[2004Tama_NMA1]]
| Flexible fitting with Normal Modes (I)
|-

| Paper
| [[2004Tama_NMA2]]
| Flexible fitting with Normal Modes (II)
|-

| Paper
| [[2005Velazquez_Superfamilies]]
| Recognition of the superfamily folding in medium-high resolution volumes
|-

| Paper
| [[2007Kleywegt_QualityControl]]
| Quality control and validation of fitting
|-

|}

=== Books and reviews ===

{|

| Book
| [[1980Herman_Tomography]]
| General book on tomography
|-

| Book
| [[1988Kak_Tomography]]
| General book on tomography
|-

| Paper
| [[2000Tao_Review]]
| Review of single particles
|-

| Paper
| [[2000VanHeel_Review]]
| Review of single particles
|-

| Paper
| [[2002Frank_Review]]
| Review of single particles
|-

| Paper
| [[2002Schmid_Review]]
| Review of single particles
|-

| Paper
| [[2004Henderson_Review]]
| Review of electron microscopy
|-

| Paper
| [[2004Subramaniam_Review]]
| Review of single particles
|-

| Paper
| [[2006Fernandez_Review]]
| Review of electron microscopy
|-

| Book
| [[2006Frank_book]]
| Book covering all aspects of electron microscopy of single particles
|-

| Paper
| [[2006Sorzano_Review]]
| Review of optimization problems in electron microscopy
|-

| Paper
| [[2007Leschziner_Review]]
| Review of 3D heterogeneity handling algorithms
|-

| Paper
| [[2007Sorzano_Review]]
| Review of the image processing steps
|-

| Paper
| [[2008Fanelli_ImageFormation]]
| Review on the image formation model from the electron waves and open inverse-problems in Electron Tomography
|-

| Paper
| [[2008Fernandez_HPCReview]]
| High performance computing in electron cryomicroscopy
|-

| Paper
| [[2008Jonic_Review]]
| Comparison between electron tomography and single particles
|-

| Paper
| [[2010DeRosier_Review]]
| Personal account of how 3DEM developed in the early days
|-

|}

=== Software ===

{|

| Paper
| [[1996Frank_Spider]]
| Spider
|-

| Paper
| [[1996VanHeel_Imagic]]
| Imagic
|-

| Paper
| [[1999Lutdke_Eman]]
| Eman
|-

| Paper
| [[2004Sorzano_Xmipp]]
| Xmipp
|-

| Paper
| [[2007Heymann_Bsoft]]
| Bsoft
|-

| Paper
| [[2008Scheres_XmippProtocols]]
| Xmipp Protocols
|-

|}

== Electron tomography ==

=== Image alignment ===

{|

| Paper
| [[2001Brandt_Automatic1]]
| Automatic alignment without fiducial markers
|-

| Paper
| [[2001Brandt_Automatic2]]
| Automatic alignment with fiducial markers
|-

| Paper
| [[2006Winkler_alignment]]
| Marker-free alignment and refinement
|-

| Paper
| [[2006Castano_alignment]]
| Alignment with non-perpendicularity
|-

| Paper
| [[2007Castano_alignment]]
| Fiducial-less alignment of cryo-sections
|-

| Paper
| [[2009Sorzano_alignment]]
| Marker-free alignment and refinement
|-

|}

=== CTF estimation and restoration ===

{|

| Paper
| [[2003Winkler_CTF]]
| Focus gradient correction in electron tomography
|-

| Paper
| [[2006Fernandez_CTF]]
| CTF determination and correction in electron tomography
|-

| Paper
| [[2009Zanetti_CTF]]
| CTF determination and correction in electron tomography
|-

| Paper
| [[2009Xiong_CTF]]
| CTF determination and correction for low dose tomographic tilt series
|-

|}

=== 3D reconstruction ===

{|

| Paper
| [[1972Gilbert_SIRT]]
| Simultaneous Iterative Reconstruction Technique (SIRT)
|-

| Paper
| [[1973Herman_ART]]
| Algebraic Reconstruction Technique (ART)
|-

| Paper
| [[1984Andersen_SART]]
| Simultaneous Algebraic Reconstruction Technique (SART)
|-

| Paper
| [[1992Radermacher_WBP]]
| Weighted Backprojection in electron tomography
|-

| Paper
| [[1997Marabini_reconstruction]]
| Iterative reconstruction in electron tomography
|-

| Paper
| [[2002Fernandez_reconstruction]]
| Iterative reconstruction in electron tomography
|-

| Paper
| [[2007Radermacher_WBP]]
| Weighted Backprojection in electron tomography
|-

| Paper
| [[2008Fernandez_CARP]]
| Component Averaged Row Projections (CARP)
|-
|}

=== Noise reduction ===
{|

| Paper
| [[2001Frangakis_NAD]]
| Noise reduction with Nonlinear Anisotropic Diffusion
|-

| Paper
| [[2003Fernandez_AND]]
| Anisotropic nonlinear diffusion for electron tomography
|-

| Paper
| [[2003Jiang_Bilateral]]
| Bilateral denoising filter in electron microscopy
|-

| Paper
| [[2005Fernandez_AND]]
| Anisotropic nonlinear denoising in electron tomography
|-

| Paper
| [[2007Heide_median]]
| Iterative median filtering in electron tomography
|-

| Paper
| [[2007Fernandez_autAND]]
| Anisotropic nonlinear diffusion with automated parameter tuning
|-

| Paper
| [[2009Fernandez_Beltrami]]
| Nonlinear filtering based on Beltrami flow
|-

|}

=== Segmentation ===

{|

| Paper
| [[2002Frangakis_Eigenanalysis]]
| Segmentation using eigenvector analysis.
|-

| Paper
| [[2002Volkmann_Watershed]]
| Segmentation using watershed transform.
|-

| Paper
| [[2003Bajaj_BoundarySegmentation]]
| Segmentation based on fast marching.
|-

| Paper
| [[2005Cyrklaff_Thresholding]]
| Segmentation using optimal thresholding.
|-

| Paper
| [[2007Lebbink_TemplateMatching]]
| Segmentation using template matching.
|-

| Paper
| [[2007Sandberg_OrientationFields]]
| Segmentation using orientation fields.
|-

| Paper
| [[2007Sandberg_SegmentationReview]]
| Review on segmentation in electron tomography.
|-

| Paper
| [[2008Garduno_FuzzySegmentation]]
| Segmentation using fuzzy set theory principles.
|-

| Paper
| [[2009Lebbink_TemplateMatching2]]
| Segmentation using template matching.
|-

|}

=== Resolution ===
{|

| Paper
| [[2005Cardone_Resolution]]
| Resolution criterion for electron tomography
|-

|}

=== Subtomogram analysis ===

{|

| Paper
| [[2000Bohm_Template]]
| Macromolecule finding by template matching
|-

| Paper
| [[2002Frangakis_Template]]
| Macromolecule finding by template matching
|-

| Paper
| [[2006Nickell_Review]]
| Review of macromolecule finding by template matching (Visual Proteomics)
|-

| Paper
| [[2007Best_Review]]
| Review of Localization of Protein Complexes by Pattern Recognition
|-

| Paper
| [[2007Forster_Review]]
| Review of structure determination by subtomogram averaging
|-

| Paper
| [[2008Forster_Classification]]
| Classification of subtomograms using constrained correlation
|-

| Paper
| [[2008Bartesaghi_Classification]]
| Classification and averaging of subtomograms
|-

| Paper
| [[2008Schmid_Averaging]]
| Alignment and averaging of subtomograms
|-

|}

=== Books and reviews ===

{|

| Paper
| [[2000Baumeister_Review]]
| Review of electron tomography
|-

| Paper
| [[2003Koster_Review]]
| Review of electron tomography
|-

| Paper
| [[2003Sali_Review]]
| Review of electron tomography
|-

| Paper
| [[2004Henderson_Review]]
| Review of electron microscopy
|-

| Paper
| [[2005Lucic_Review]]
| Review of electron tomography
|-

| Paper
| [[2006Fernandez_Review]]
| Review of electron microscopy
|-

| Book
| [[2006Frank_TomoBook]]
| Electron Tomography
|-

| Book
| [[2007McIntosh_Book]]
| Cellular Electron Microscopy
|-

| Paper
| [[2007Sorzano_Review]]
| Review of the image processing steps
|-

| Paper
| [[2008Fanelli_ImageFormation]]
| Review on the image formation model from the electron waves and open inverse-problems
|-

| Paper
| [[2008Fernandez_HPCReview]]
| High performance computing in electron cryomicroscopy
|-

| Paper
| [[2008Jonic_Review]]
| Comparison between electron tomography and single particles
|-

|}

=== Software ===

{|

| Paper
| [[1996Kremer_IMOD]]
| IMOD
|-

| Paper
| [[1996Chen_Priism/IVE]]
| Priism/IVE
|-

| Paper
| [[1996Frank_Spider]]
| Spider
|-

| Paper
| [[2004Sorzano_Xmipp]]
| Xmipp
|-

| Paper
| [[2005Nickell_TOM]]
| TOM Toolbox
|-

| Paper
| [[2007Messaoudi_TomoJ]]
| TomoJ
|-

| Paper
| [[2008Heymann_BsoftTomo]]
| Bsoft
|-

|}

== 2D Crystals ==

=== 2D Preprocessing ===

{|

| Paper
| [[1986Henderson_Processing]]
| General 2D processing
|-

| Paper
| [[2000He_PhaseAlignment]]
| Phase consistency and Alignment
|-

| Paper
| [[2006Gil_Unbending]]
| Crystal unbending
|-

|}

=== Classification ===
{|

| Paper
| [[1988Frank_Classification]]
| MSA and classification in electron crystallography
|-

| Paper
| [[1996Fernandez_SOM]]
| Classification based on self organizing maps
|-

| Paper
| [[1998Sherman_MSA]]
| Classification based on MSA
|-

|}
=== 3D Reconstruction ===

{|

| Paper
| [[1985Wang_Solvent]]
| Solvent flattening
|-

| Paper
| [[1990Henderson_Processing]]
| General 3D processing
|-

| Paper
| [[2004Marabini_ART]]
| Algebraic Reconstruction Technique with blobs for crystals (Xmipp)
|-

|}

=== Books and reviews ===

{|

| Paper
| [[1998Walz_Review]]
| Review of 2D crystallography
|-

| Paper
| [[1999Glaeser_Review]]
| Review of 2D crystallography
|-

| Paper
| [[2001Ellis_Review]]
| Review of 2D crystallography
|-

| Paper
| [[2001Glaeser_Review]]
| Review of 2D crystallography
|-

| Paper
| [[2004Henderson_Review]]
| Review of electron microscopy
|-

| Paper
| [[2006Fernandez_Review]]
| Review of single particles, electron tomography and crystallography
|-

| Paper
| [[2007Sorzano_Review]]
| Review of the image processing steps
|-

|}

=== Software ===

{|

| Paper
| [[1996Crowther_MRC]]
| MRC
|-

| Paper
| [[2004Sorzano_Xmipp]]
| Xmipp
|-

| Paper
| [[2007Gipson_2dx]]
| 2dx
|-

| Paper
| [[2007Heymann_Bsoft]]
| Bsoft
|-

| Paper
| [[2007Philippsen_IPLT]]
| IPLT
|-

|}

== Helical particles ==

=== Filament corrections ===

{|

| Paper
| [[1986Egelman_Curved]]
| Algorithm for correcting curved filaments
|-

| Paper
| [[1988Bluemke_Pitch]]
| Algorithm for correcting filaments with different helical pitches
|-

| Paper
| [[2006Wang_Pitch]]
| Algorithm for correcting filaments with different helical pitches
|-

|}

=== Reconstruction ===

{|

| Paper
| [[1958Klug_Fourier]]
| Fourier Bessel decomposition of the projection images
|-

| Paper
| [[1970DeRosier_Rec]]
| Image processing steps towards 3D reconstruction
|-

| Paper
| [[1992Morgan_Rec]]
| Image processing steps towards 3D reconstruction
|-

| Paper
| [[2005Wang_Iterative]]
| Iterative Fourier-Bessel algorithm
|-

| Paper
| [[2007Egelman_Iterative]]
| Iterative real-space algorithm
|-

|}

=== Books and reviews ===

{|

| Paper
| [[1970DeRosier_Rec]]
| Image processing steps towards 3D reconstruction
|-

| Paper
| [[1992Morgan_Rec]]
| Image processing steps towards 3D reconstruction
|-

| Paper
| [[2004Henderson_Review]]
| Review of electron microscopy
|-

| Paper
| [[2007Sorzano_Review]]
| Review of the image processing steps
|-

|}

=== Software ===

{|

| Paper
| [[1996Carragher_Phoelix]]
| Phoelix
|-

| Paper
| [[1996Crowther_MRC]]
| MRC
|-

| Paper
| [[1996Owen_Brandeis]]
| Brandeis
|-

|}

== Icosahedral particles ==

=== Reconstruction ===

{|

| Paper
| [[1970Crowther_Rec]]
| Reconstruction of icosahedral viruses in Fourier space
|-

| Paper
| [[1971Crowther_Rec]]
| Reconstruction of icosahedral viruses in Fourier space
|-

| Paper
| [[1996Fuller_Rec]]
| Reconstruction of icosahedral viruses in Fourier space
|-

| Paper
| [[1997Thuman_Rec]]
| Reconstruction of icosahedral viruses in Fourier space
|-

|}

=== Classification ===

{|

| Paper
| [[2005Scheres_Virus]]
| Classification of virus capsids in real space
|-

|}

=== Books and reviews ===

{|

| Paper
| [[1999Baker_Review]]
| Review of reconstruction of icosahedral viruses
|-

| Paper
| [[1999Conway_Review]]
| Review of reconstruction of icosahedral viruses
|-

| Paper
| [[2000Thuman_Review]]
| Review of reconstruction of icosahedral viruses
|-

| Paper
| [[2003Lee_Review]]
| Review of reconstruction of icosahedral viruses
|-

| Paper
| [[2003Navaza_Review]]
| Review of reconstruction of icosahedral viruses
|-

| Paper
| [[2006Grunewald_Review]]
| Review of reconstruction of icosahedral viruses
|-

|}

=== Software ===

{|

| Paper
| [[1996Baker_EMPFT]]
| EMPFT
|-

| Paper
| [[1996Crowther_MRC]]
| MRC
|-

| Paper
| [[1996Frank_Spider]]
| Spider
|-

| Paper
| [[1996VanHeel_Imagic]]
| Imagic
|-

| Paper
| [[2004Sorzano_Xmipp]]
| Xmipp
|-

|}

== Data bases ==

{|

| Paper
| [[2003Boutselakis_EMSD]]
| EMSD database
|-

| Paper
| [[2005Heymann_Conventions]]
| Conventions for software interoperability
|-

|}

== Relationship to other structural information sources ==

{|

| Paper
| [[2000Engel_AFM]]
| Review of Atomic Force Microscopy
|-

| Paper
| [[2001Dimmeler_AFM]]
| Constraints from Atomic Force Microscopy
|-

| Paper
| [[2003Mobus_EnergyLoss]]
| Chemical mapping by energy loss electron tomography
|-

| Paper
| [[2004Leapman_EnergyLoss]]
| Chemical mapping by energy loss electron tomography
|-

| Paper
| [[2004Leapman_Review]]
| Review on correlative microscopy
|-

| Paper
| [[2005Boudier_EFTETJ]]
| Software for Chemical mapping by energy loss electron tomography
|-

| Paper
| [[2005Vestergaard_SAXS]]
| Example of comparison of 3DEM and Small-angle X-ray scattering
|-

| Paper
| [[2007Hamada_SAXS]]
| Constraints from Small-angle X-ray scattering
|-

|}

== Mathematical tools necessary ==

== People developing methods ==
Please, add yourself to this list (due to privacy reasons, please, do not add anyone else to the list without his/her explicit consent). Sort by first name alphabetical order.

[http://biocomp.cnb.csic.es/~coss Carlos Oscar S. Sorzano]: CSIC, Madrid, Spain<br>

[http://www.curie.fr/recherche/themes/detail_equipe.cfm/lang/_fr/id_equipe/241.htm Cédric Messaoudi]: Institute Curie, Paris, France<br>

[mailto:jrbcast@gmail.com José Román Bilbao-Castro]: UAL, Almería, Spain; CSIC, Madrid, Spain<br>

== 3DEM sites ==
* [http://3dem.ucsd.edu/ 3DEM web site]

* [http://en.wikibooks.org/wiki/Software_Tools_For_Molecular_Microscopy Software tools for molecular microscopy]

* [http://www.emdatabank.org/ The Electron Microscopy Data Bank (EMDB)]

* [http://ccdb.ucsd.edu The Cell Centered Database (CCDB)]

* [http://conventions.cnb.csic.es The geometrical software conventions web page ]

== Editing useful links ==

* [http://www.mediawiki.org/wiki/Help:Formatting Text formatting in Mediawiki]
* [http://www.mediawiki.org/wiki/Help:Links Adding links in Mediawiki]
* [http://www.mediawiki.org/wiki/Help:Images Adding images in Mediawiki]
* [http://www.mediawiki.org/wiki/Help:Tables Making tables in Mediawiki]

2009Xiong CTF

2009-10-28T12:22:01Z

Jjfdez: /* Related methods */

== Citation ==
Xiong Q, Morphew MK, Schwartz CL, Hoenger AH, Mastronarde DN. CTF determination and correction for low dose tomographic tilt series. Journal of Structural Biology 2009 168:378-387

== Abstract ==
The resolution of cryo-electron tomography can be limited by the first zero of the microscope’s contrast transfer function (CTF). To achieve higher resolution, it is critical to determine the CTF and correct its phase inversions. However, the extremely low signal-to-noise ratio (SNR) and the defocus gradient in the projections of tilted specimens make this process challenging. Two programs, CTFPLOTTER and CTFPHASEFLIP, have been developed to address these issues. CTFPLOTTER obtains a 1D power spectrum by periodogram averaging and rotational averaging and it estimates the noise background with a novel approach, which uses images taken with no specimen. The background-subtracted 1D power spectra from image regions at different defocus values are then shifted to align their first zeros and averaged together. This averaging improves the SNR sufficiently that it becomes possible to determine the defocus for subsets of the tilt series rather than just the entire series. CTFPHASEFLIP corrects images line-by-line by inverting phases appropriately in thin strips of the image at nearly constant defocus. CTF correction by these methods is shown to improve the resolution of aligned, averaged particles extracted from tomograms. However, some restoration of Fourier amplitudes at high frequencies is important for seeing the benefits from CTF correction.

== Keywords ==
Electron tomography; Contrast transfer function; Cryomicroscopy; Software

== Links ==
Article: http://dx.doi.org/10.1016/j.jsb.2009.08.016

== Related software ==
[http://bio3d.colorado.edu/imod/ IMOD]

== Related methods ==
CTF determination and correction in electron tomography [[2006Fernandez_CTF]]

== Comments ==

2009Xiong CTF

2009-10-28T12:21:50Z

Jjfdez: /* Related methods */

== Citation ==
Xiong Q, Morphew MK, Schwartz CL, Hoenger AH, Mastronarde DN. CTF determination and correction for low dose tomographic tilt series. Journal of Structural Biology 2009 168:378-387

== Abstract ==
The resolution of cryo-electron tomography can be limited by the first zero of the microscope’s contrast transfer function (CTF). To achieve higher resolution, it is critical to determine the CTF and correct its phase inversions. However, the extremely low signal-to-noise ratio (SNR) and the defocus gradient in the projections of tilted specimens make this process challenging. Two programs, CTFPLOTTER and CTFPHASEFLIP, have been developed to address these issues. CTFPLOTTER obtains a 1D power spectrum by periodogram averaging and rotational averaging and it estimates the noise background with a novel approach, which uses images taken with no specimen. The background-subtracted 1D power spectra from image regions at different defocus values are then shifted to align their first zeros and averaged together. This averaging improves the SNR sufficiently that it becomes possible to determine the defocus for subsets of the tilt series rather than just the entire series. CTFPHASEFLIP corrects images line-by-line by inverting phases appropriately in thin strips of the image at nearly constant defocus. CTF correction by these methods is shown to improve the resolution of aligned, averaged particles extracted from tomograms. However, some restoration of Fourier amplitudes at high frequencies is important for seeing the benefits from CTF correction.

== Keywords ==
Electron tomography; Contrast transfer function; Cryomicroscopy; Software

== Links ==
Article: http://dx.doi.org/10.1016/j.jsb.2009.08.016

== Related software ==
[http://bio3d.colorado.edu/imod/ IMOD]

== Related methods ==
[CTF determination and correction in electron tomography [[2006Fernandez_CTF]]]

== Comments ==

2009Xiong CTF

2009-10-28T12:21:39Z

Jjfdez: /* Related methods */

2009Xiong CTF

2009-10-28T12:21:21Z

Jjfdez: /* Related methods */

== Citation ==
Xiong Q, Morphew MK, Schwartz CL, Hoenger AH, Mastronarde DN. CTF determination and correction for low dose tomographic tilt series. Journal of Structural Biology 2009 168:378-387

== Abstract ==
The resolution of cryo-electron tomography can be limited by the first zero of the microscope’s contrast transfer function (CTF). To achieve higher resolution, it is critical to determine the CTF and correct its phase inversions. However, the extremely low signal-to-noise ratio (SNR) and the defocus gradient in the projections of tilted specimens make this process challenging. Two programs, CTFPLOTTER and CTFPHASEFLIP, have been developed to address these issues. CTFPLOTTER obtains a 1D power spectrum by periodogram averaging and rotational averaging and it estimates the noise background with a novel approach, which uses images taken with no specimen. The background-subtracted 1D power spectra from image regions at different defocus values are then shifted to align their first zeros and averaged together. This averaging improves the SNR sufficiently that it becomes possible to determine the defocus for subsets of the tilt series rather than just the entire series. CTFPHASEFLIP corrects images line-by-line by inverting phases appropriately in thin strips of the image at nearly constant defocus. CTF correction by these methods is shown to improve the resolution of aligned, averaged particles extracted from tomograms. However, some restoration of Fourier amplitudes at high frequencies is important for seeing the benefits from CTF correction.

== Keywords ==
Electron tomography; Contrast transfer function; Cryomicroscopy; Software

== Links ==
Article: http://dx.doi.org/10.1016/j.jsb.2009.08.016

== Related software ==
[http://bio3d.colorado.edu/imod/ IMOD]

== Related methods ==
[CTF determination and correction in electron tomography [2006Fernandez_CTF]]

== Comments ==

2009Xiong CTF

2009-10-28T12:20:33Z

Jjfdez: /* Related methods */

== Citation ==
Xiong Q, Morphew MK, Schwartz CL, Hoenger AH, Mastronarde DN. CTF determination and correction for low dose tomographic tilt series. Journal of Structural Biology 2009 168:378-387

== Abstract ==
The resolution of cryo-electron tomography can be limited by the first zero of the microscope’s contrast transfer function (CTF). To achieve higher resolution, it is critical to determine the CTF and correct its phase inversions. However, the extremely low signal-to-noise ratio (SNR) and the defocus gradient in the projections of tilted specimens make this process challenging. Two programs, CTFPLOTTER and CTFPHASEFLIP, have been developed to address these issues. CTFPLOTTER obtains a 1D power spectrum by periodogram averaging and rotational averaging and it estimates the noise background with a novel approach, which uses images taken with no specimen. The background-subtracted 1D power spectra from image regions at different defocus values are then shifted to align their first zeros and averaged together. This averaging improves the SNR sufficiently that it becomes possible to determine the defocus for subsets of the tilt series rather than just the entire series. CTFPHASEFLIP corrects images line-by-line by inverting phases appropriately in thin strips of the image at nearly constant defocus. CTF correction by these methods is shown to improve the resolution of aligned, averaged particles extracted from tomograms. However, some restoration of Fourier amplitudes at high frequencies is important for seeing the benefits from CTF correction.

== Keywords ==
Electron tomography; Contrast transfer function; Cryomicroscopy; Software

== Links ==
Article: http://dx.doi.org/10.1016/j.jsb.2009.08.016

== Related software ==
[http://bio3d.colorado.edu/imod/ IMOD]

== Related methods ==
[[2006Fernandez_CTF]]
| CTF determination and correction in electron tomography

== Comments ==

2009Xiong CTF

2009-10-28T12:20:03Z

Jjfdez: /* Related software */

1996Kremer IMOD

2009-10-28T12:19:37Z

Jjfdez: /* Related software */

== Citation ==

Kremer JR, Mastronarde DN, McIntosh JR (1996) Computer visualization
of three-dimensional image data using IMOD. J Struct Biol
116:71–76

== Abstract ==

We have developed a computer software package, IMOD, as a tool for analyzing and viewing three-dimensional biological image data. IMOD is useful for studying and modeling data from tomographic, serial section, and optical section reconstructions. The software allows image data to be visualized by several different methods. Models of the image data can be visualized by volume or contour surface rendering and can yield quantitative information.

== Keywords ==

Software package, electron tomography

== Links ==

Article http://linkinghub.elsevier.com/retrieve/pii/S1047847796900131

== Related software ==
[http://bio3d.colorado.edu/imod/ IMOD]

== Related methods ==

== Comments ==

1996Kremer IMOD

2009-10-28T12:18:37Z

Jjfdez: /* Related software */

== Citation ==

Kremer JR, Mastronarde DN, McIntosh JR (1996) Computer visualization
of three-dimensional image data using IMOD. J Struct Biol
116:71–76

== Abstract ==

We have developed a computer software package, IMOD, as a tool for analyzing and viewing three-dimensional biological image data. IMOD is useful for studying and modeling data from tomographic, serial section, and optical section reconstructions. The software allows image data to be visualized by several different methods. Models of the image data can be visualized by volume or contour surface rendering and can yield quantitative information.

== Keywords ==

Software package, electron tomography

== Links ==

Article http://linkinghub.elsevier.com/retrieve/pii/S1047847796900131

== Related software ==
[IMOD http://biocomp.cnb.csic.es/3DEM-Methods/index.php/1996Kremer_IMOD]

== Related methods ==

== Comments ==

1996Kremer IMOD

2009-10-28T12:18:13Z

Jjfdez: /* Related software */

== Citation ==

Kremer JR, Mastronarde DN, McIntosh JR (1996) Computer visualization
of three-dimensional image data using IMOD. J Struct Biol
116:71–76

== Abstract ==

We have developed a computer software package, IMOD, as a tool for analyzing and viewing three-dimensional biological image data. IMOD is useful for studying and modeling data from tomographic, serial section, and optical section reconstructions. The software allows image data to be visualized by several different methods. Models of the image data can be visualized by volume or contour surface rendering and can yield quantitative information.

== Keywords ==

Software package, electron tomography

== Links ==

Article http://linkinghub.elsevier.com/retrieve/pii/S1047847796900131

== Related software ==
[IMOD https://biocomp.cnb.csic.es/3DEM-Methods/index.php/1996Kremer_IMOD]

== Related methods ==

== Comments ==

2009Xiong CTF

2009-10-28T12:16:54Z

Jjfdez:

2009Zanetti CTF

2009-10-02T10:44:22Z

Jjfdez:

== Citation ==
Zanetti G, Riches JD, Fuller SD, Briggs JAG. Contrast transfer function correction applied to cryo-electron tomography and sub-tomogram averaging. Journal of Structural Biology 2009 168:305-312

== Abstract ==
Cryo-electron tomography together with averaging of sub-tomograms containing identical particles can reveal the structure of proteins or protein complexes in their native environment. The resolution of this technique is limited by the contrast transfer function (CTF) of the microscope. The CTF is not routinely corrected in cryo-electron tomography because of difficulties including CTF detection, due to the low signal to noise ratio, and CTF correction, since images are characterised by a spatially variant CTF. Here we simulate the effects of the CTF on the resolution of the final reconstruction, before and after CTF correction, and consider the effect of errors and approximations in defocus determination. We show that errors in defocus determination are well tolerated when correcting a series of tomograms collected at a range of defocus values. We apply methods for determining the CTF parameters in low signal to noise images of tilted specimens, for monitoring defocus changes using observed magnification changes, and for correcting the CTF prior to reconstruction. Using bacteriophage PRD1 as a test sample, we demonstrate that this approach gives an improvement in the structure obtained by sub-tomogram averaging from cryo-electron tomograms.

== Keywords ==
Cryo-electron tomography; Sub-tomogram averaging; CTF correction; PRD1

== Links ==
Article: http://dx.doi.org/10.1016/j.jsb.2009.08.002

== Related software ==

== Related methods ==

== Comments ==

2007Fernandez autAND

2009-09-08T09:05:50Z

Jjfdez:

== Citation ==
Fernandez JJ, Li S, Lucic V. Three-dimensional anisotropic noise reduction with automated parameter tuning. Application to electron cryotomography. Lecture Notes in Computer Science, 4788:60-69, 2007.

== Abstract ==
This article presents an approach for noise filtering that is based on anisotropic nonlinear diffusion. The method combines edge-preserving noise reduction with a strategy to enhance local structures and a mechanism to further smooth the background. We have provided the method with an automatic mechanism for parameter self-tuning and for stopping the iterative filtering process. The performance of the approach is illustrated with its application to electron cryotomography (cryoET). CryoET has emerged as a leading imaging technique for visualizing the molecular architecture of complex biological specimens. A challenging computational task in this discipline is to increase the extremely low signal-to-noise ratio (SNR) to allow visualization and interpretation of the three-dimensional structures. The filtering method here proposed succeeds in substantially reducing the noise with excellent preservation of the structures.

== Keywords ==
Electron tomography; Denoising; Anisotropic nonlinear diffusion

== Links ==
Article: http://dx.doi.org/10.1007/978-3-540-75271-4_7

== Related software ==
[http://www.ual.es/~jjfdez/SW/tomoand.html TOMOAND]

== Related methods ==

== Comments ==

1984Andersen SART

2009-08-07T15:54:14Z

Jjfdez:

== Citation ==
A.H. Andersen, A.C. Kak. Simultaneous Algebraic Reconstruction Technique (SART): A superior implementation of the ART algorithm. Ultrasonic Imaging 6:81-94, 1984

== Abstract ==
In this paper we have discussed what appears to be a superior implementation of the Algebraic Reconstruction Technique (ART). The method is based on 1) simultaneous application of the error correction terms as computed by ART for all rays in a given projection; 2) longitudinal weighting of the correction terms back-distributed along the rays; and 3) using bilinear elements for discrete approximation to the ray integrals of a continuous image. Since this implementation generates a good reconstruction in only one iteration, it also appears to have a computational advantage over the more traditional implementation of ART. Potential applications of this implementation include image reconstruction in conjunction with ray tracing for ultrasound and microwave tomography in which the curved nature of the rays leads to a non-uniform ray density across the image.

== Keywords ==
Algebraic reconstruction; digital ray tracing; tomography; ultrasound

== Links ==
Article: http://dx.doi.org/10.1016/0161-7346(84)90008-7

== Related software ==

== Related methods ==

== Comments ==

2008Fernandez CARP

2009-08-07T15:51:29Z

Jjfdez:

== Citation ==
J.J. Fernandez, D. Gordon, R. Gordon. Efficient parallel implementation of iterative reconstruction algorithms for electron tomography. Journal of Parallel and Distributed Computing 68:626-640, 2008.

== Abstract ==
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.

== Keywords ==
BICAV; CARP; CAV; Component-averaging; Electron microscopy; Electron tomography; Image reconstruction; Parallel processing; WBP; Weighted back-projection

== Links ==
Article: http://dx.doi.org/10.1016/j.jpdc.2007.09.003

== Related software ==

== Related methods ==

== Comments ==

2000He Phase

2009-08-07T10:02:40Z

Jjfdez: 2000He Phase moved to 2000He PhaseAlignment

#REDIRECT [[2000He PhaseAlignment]]

2000He PhaseAlignment

2009-08-07T10:02:40Z

Jjfdez: 2000He Phase moved to 2000He PhaseAlignment

== Citation ==
He WZ, Carazo JM, Fernandez JJ. A new phase consistency criterion and its application in electron crystallography. Ultramicroscopy 85:73-91, 2000.

== Abstract ==

In this work, we present the principles and potential advantages of a methodology to assess Fourier components in terms of phase consistency. We define a new phase consistency criterion among sets of spatially translated images based upon a novel conception of the spatial shift property of the Fourier transform. The article shows how this criterion can be used in the alignment stage of the 3D reconstruction process with a two-fold objective: Assessment of the frequency components and robustness in the alignment. In that sense, the article shows and analyzes the results obtained from the application of the new index of quality in the context of projection image alignment. We have focussed our attention on the electron crystallography field, by applying such a phase consistency definition over image reflections. The results that have been obtained show that the new phase-consistency definition may complement the traditional SNR-based index of quality (commonly known as IQ) of reflections. As a consequence, the reliability of the alignment may be improved by discarding those reflections judged as non-reliable according to the phase-consistency criterion.

== Keywords ==

Data processing/image processing; Three-dimensional reconstruction

== Links ==

Articles http://dx.doi.org/10.1016/S0304-3991(00)00047-4

== Related software ==

== Related methods ==

== Comments ==

2000He PhaseAlignment

2009-08-07T10:02:29Z

Jjfdez:

1988Frank Classification

2009-08-07T09:58:20Z

Jjfdez:

== Citation ==

Frank J, Chiu W, Degn L. The characterization of structural variations within a crystal field. Ultramicroscopy 26:345-360, 1988.

== Abstract ==

The technique of correlation averaging is refined by the use of multivariate statistical analysis and classification. The refined method can deal with the presence of structural variations within a crystal field. A low-dose image of a crotoxin crystal embedded in ice is used to demonstrate that crystallographic structural parameters characterizing the different areas of such a crystal with varying structure can be extracted rigorously and reproducibly.

== Keywords ==

== Links ==

Articles http://dx.doi.org/10.1016/0304-3991(88)90234-3

== Related software ==

== Related methods ==

== Comments ==

1996Fernandez SOM

2009-08-07T09:56:51Z

Jjfdez: /* Citation */

== Citation ==

Fernandez JJ, Carazo, JM. Analysis of structural variability within two-dimensional biological crystals by a combination of patch averaging techniques and self organizing maps. Ultramicroscopy 65:81-93, 1996

== Abstract ==

We study in this work the use of self organizing maps to analyze the structural variability that can be found along two-dimensional crystals of biological macromolecules. Small areas of the crystals, termed “patches” by previous researchers, are used to obtain local average images that are then used as the input of a Self Organizing Map. This procedure allows for a fast and accurate image classification. Multivariate Statistical Analysis is then used on the resulting code vectors producing a very condensed data representation. This methodology is applied to previously studied crystals of bacteriophage φ29 p10 connector, finding a crystalline heterogeneity probably associated to multilayers in some areas of the crystal.

== Keywords ==

Image processing

== Links ==

Articles http://dx.doi.org/10.1016/S0304-3991(96)00063-0

== Related software ==

== Related methods ==

== Comments ==

1996Fernandez SOM

2009-08-07T09:56:36Z

Jjfdez:

== Citation ==

Analysis of structural variability within two-dimensional biological crystals by a combination of patch averaging techniques and self organizing maps. Ultramicroscopy 65:81-93, 1996

== Abstract ==

We study in this work the use of self organizing maps to analyze the structural variability that can be found along two-dimensional crystals of biological macromolecules. Small areas of the crystals, termed “patches” by previous researchers, are used to obtain local average images that are then used as the input of a Self Organizing Map. This procedure allows for a fast and accurate image classification. Multivariate Statistical Analysis is then used on the resulting code vectors producing a very condensed data representation. This methodology is applied to previously studied crystals of bacteriophage φ29 p10 connector, finding a crystalline heterogeneity probably associated to multilayers in some areas of the crystal.

== Keywords ==

Image processing

== Links ==

Articles http://dx.doi.org/10.1016/S0304-3991(96)00063-0

== Related software ==

== Related methods ==

== Comments ==

1998Sherman MSA

2009-08-07T09:55:14Z

Jjfdez: /* Citation */

== Citation ==

M.B. Sherman, T. Soejima, W. Chiu, M. van Heel. Multivariate analysis of single unit cells in electron crystallography. Ultramicroscopy 74:179-199, 1998

== Abstract ==

High-resolution electron cryomicroscopy of two-dimensional protein crystals is associated with extremely noisy raw data in which even the crystal lattice often cannot be discerned. Correlation averaging procedures, aimed at calculating the total average of all unit cells of crystals in order to reduce noise, are now used routinely in electron crystallography. Multivariate statistical analysis (MSA) may be used for finding not only the average structure but also for quantifying the systematic departures from that average within the population of individual unit cells. We show that the MSA approach is applicable to single unit-cell images in the low-dose (<10 electrons/Å2), high-resolution (<5 Å) realm using 400 keV electron spot-scan images of ice-embedded gp32*I protein crystals. Our feasibility study opens a pathway toward exploiting these naturally occurring variations on the unit-cell theme in order to achieve higher-resolution three-dimensional reconstruction results, or to better understand the dynamic behaviour of molecules within two-dimensional crystals. We explain how single unit-cell images can be processed and classified into homogeneous groups, and we review how the results of such discriminate averaging may subsequently be exploited within the context of conventional “h, k”-space electron crystallographic approaches. Variations among the individual unit cells may thus be one of the most significant resolution-limiting factors currently experienced in electron crystallography. The quantitative assessment and exploitation of such variations may lead to an increased performance of electron crystallographic procedures.

== Keywords ==

MSA; Correlation averaging; Automatic classification; Electron crystallography; gp32*I; Electron cryomicroscopy

== Links ==

Articles http://dx.doi.org/10.1016/S0304-3991(98)00041-2

== Related software ==

== Related methods ==

== Comments ==

1998Sherman MSA

2009-08-07T09:55:05Z

Jjfdez:

1990Henderson Processing

2009-08-07T09:43:48Z

Jjfdez:

== Citation ==
R. Henderson, J.M. Baldwin, T.A. Ceska, F. Zemlin, E. Beckmann, K.H. Downing. Model for the structure of bacteriorhodopsin based on high-resolution electron cryo-microscopy. Journal of Molecular Biology, Volume 213, Issue 4, 20 June 1990, Pages 899-929

== Abstract ==

The light-driven proton pump-bacteriorhodopsin occurs naturally as two-dimensional crystals. A three-dimensional density map of the structure, at near-atomic resolution, has been obtained by studying the crystals using electron cryo-microscopy to obtain electron diffraction patterns and high-resolution micrographs.

New methods were developed for analysing micrographs from tilted specimens, incorporating methods previously developed for untilted specimens that enable large areas to be analysed and corrected for distortions. Data from 72 images, from both tilted and untilted specimens, were analysed to produce the phases of 2700 independent Fourier components of the structure. The amplitudes of these components were accurately measured from 150 diffraction patterns. Together, these data represent about half of the full three-dimensional transform to 3·5 Å.

The map of the structure has a resolution of 3·5 Å in a direction parallel to the membrane plane but lower than this in the perpendicular direction. It shows many features in the density that are resolved from the main density of the seven α-helices. We interpret these features as the bulky aromatic side-chains of phenylalanine, tyrosine and tryptophan residues. There is also a very dense feature, which is the β-ionone ring of the retinal chromophore. Using these bulky side-chains as guide points and taking account of bulges in the helices that indicate smaller side-chains such as leucine, a complete atomic model for bacteriorhodopsin between amino acid residues 8 and 225 has been built. There are 21 amino acid residues, contributed by all seven helices, surrounding the retinal and 26 residues, contributed by five helices, forming the proton pathway or channel. Ten of the amino acid residues in the middle of the proton channel are also part of the retinal binding site.

The model also provides a useful basis for consideration of the mechanism of proton pumping and allows a consistent interpretation of a great deal of other experimental data. In particular, the structure suggests that pK changes in the Schiff base must act as the means by which light energy is converted into proton pumping pressure in the channel. Asp96 is on the pathway from the cytoplasm to the Schiff base and Asp85 is on the pathway from the Schiff base to the extracellular surface.

== Keywords ==

== Links ==

Articles http://dx.doi.org/10.1016/S0022-2836(05)80271-2

== Related software ==

== Related methods ==

== Comments ==

1986Henderson Processing

2009-08-07T09:37:01Z

Jjfdez:

== Citation ==
R Henderson, JM Baldwin, KH Downing, J Lepault, F Zemlin. Structure of purple membrane from halobacterium halobium: recording, measurement and evaluation of electron micrographs at 3.5 Å resolution. Ultramicroscopy 19:147-178, 1986.

== Abstract ==

Electron micrographs of the purple membrane have been recorded using liquid nitrogen and liquid helium cooling on three cryoelectron microscopes. The best micrographs show optical diffraction spots, arising from the two-dimensional crystal, out to resolutions of around 6 Å. Large areas of several of these micrographs have been analysed using a procedure which determines the strength of the very weak high resolution Fourier components of the image of the crystal. The procedure consists of reciprocal space filtering followed by real space correlation analysis to characterise image distortions, removal of the distortions by interpolation, and finally extraction of the amplitudes and phases of the Fourier components from the distortion-corrected image of the crystal. These raw image amplitudes and phases are then used, together with previously measured amplitude and phase information, to refine the beam tilt and crystal tilt, phase origin and amount of defocus and astigmatism of the image. The phases can then be corrected for the effects of the contrast transfer function, beam tilt and phase origin. The amplitudes of all the spots which are expected to be strong from their known electron diffraction intensity are observed to be significantly above the background noise level, and the independent phases from different images, and from symmetry-related directions in the same image, show excellent agreement out to a resolution of 3.5 Å. Although only images from untilted or slightly tilted ( < 5°) crystals have been analysed using the procedure described in this paper, a simple additional step enables analysis of images at any tilt angle, providing a complete practical method for high resolution analysis of images of two-dimensional crystalline arrays.

== Keywords ==

== Links ==

Articles http://dx.doi.org/10.1016/0304-3991(86)90203-2

== Related software ==

== Related methods ==

== Comments ==

2007Castano alignment

2009-08-07T08:48:44Z

Jjfdez:

== Citation ==

Castaño-Díez D, Al-Amoudi A, Glynn AM, Seybert A, Frangakis AS. Fiducial-less alignment of cryo-sections. J Struct Biol. 2007 Sep;159(3):413-23

== Abstract ==

Cryo-electron tomography of vitreous sections is currently the most promising technique for visualizing arbitrary regions of eukaryotic cells or tissue at molecular resolution. Despite significant progress in the sample preparation techniques over the past few years, the three dimensional reconstruction using electron tomography is not as simple as in plunge frozen samples for various reasons, but mainly due to the effects of irradiation on the sections and the resulting poor alignment. Here, we present a new algorithm, which can provide a useful three-dimensional marker model after investigation of hundreds to thousands of observations calculated using local cross-correlation throughout the tilt series. The observations are chosen according to their coherence to a particular model and assigned to virtual markers. Through this type of measurement a merit figure can be calculated, precisely estimating the quality of the reconstruction. The merit figures of this alignment method are comparable to those obtained with plunge frozen samples using fiducial gold markers. An additional advantage of the algorithm is the implicit detection of areas in the sections that behave as rigid bodies and can thus be properly reconstructed.

== Keywords ==

Electron tomography; Image processing; CEMOVIS

== Links ==

Article http://dx.doi.org/10.1016/j.jsb.2007.04.014

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== Related methods ==

== Comments ==

2006Castano alignment

2009-08-07T08:47:37Z

Jjfdez:

== Citation ==
Castano-Diez D, Seybert A, Frangakis AS. Tilt-series and electron microscope alignment for the correction of the non-perpendicularity of beam and tilt-axis. J Struct Biol. 2006 May;154(2):195-205.

== Abstract ==

In electron tomography the sample is tilted in the electron microscope and projections are recorded at different viewing angles. In the correct geometric setting, the tilt-axis of the object under scrutiny is perpendicular to the beam direction. However, we will demonstrate that this does not necessarily apply to all electron microscopes equipped with the default column alignment. The resulting effect is that a conical tilt is performed, which has to be considered in the reconstruction to avoid artifacts and to improve the resolution. A novel solution, with significantly improved convergence properties, will be introduced for calculating the three-dimensional marker model, which is necessary for the alignment of the tilt-series. Thereby, the angle between the beam direction and the tilt-axis is calculated, together with other geometrical distortions, like magnification and rotation changes, and incorporated in the reconstruction. Hereby, artifacts can be eliminated at the image processing basis, and the resolution can be significantly improved at the medium to high range frequencies. Synthetical and real data are used to demonstrate the obstructions caused by this effect and the quality improvement of the reconstructions. Finally, we also present a way to align the hardware of the microscope to correct for the non-perpendicularity between the beam direction and the tilt-axis, which is specifically tailored for tomographic applications.

== Keywords ==

Electron tomography; Alignment; Three-dimensional marker model; Image processing

== Links ==

Article http://dx.doi.org/10.1016/j.jsb.2005.12.009

== Related software ==

== Related methods ==

== Comments ==

2008Schmid Averaging

2009-08-07T08:41:19Z

Jjfdez:

== Citation ==

Schmid MF, Booth CR. Methods for aligning and for averaging 3D volumes with missing data. J Struct Biol. 2008 Mar;161(3):243-8.

== Abstract ==

The visibility and resolution of a tomographic reconstruction containing multiple copies of discrete particles can be enhanced by averaging subtomograms after they are corrected aligned. However, the “missing wedge” in electron tomography can easily lead to erroneous alignment. We have explored a Fourier space cross-correlation method with a proper weighting scheme to align and average different sets of volumetric data, each of which has different missing data due to the limited specimen tilts. This approach depends neither on a preexisting template, nor an exact knowledge of the geometry, orientation, or amount of the missing data. This paper introduces a procedure where the missing data might be gradually “filled in” by consecutively aligning and averaging volumes with different orientations of their missing data. We have validated these techniques by a set of simulated data with various symmetries and extent of missing data. We have also successfully applied these procedures to experimental cryo-electron tomographic data [Chang, J.T., Schmid, M.F., Rixon, F.J., and Chiu, W., 2007. Electron cryotomography reveals the portal in the herpesvirus capsid. J. Virol. 81, 2065–2068; Schmid, M.F., Paredes, A.M., Khant, H.A., Soyer, F., Aldrich, H.C., Chiu, W., and Shively, J.M., 2006. Structure of Halothiobacillus neapolitanus carboxysomes by cryo-electron tomography. J. Mol. Biol. 364, 526–535].

== Keywords ==

Cryo-electron tomography; Computational methods; Aligning and averaging; Electron cryotomography

== Links ==

Article http://dx.doi.org/10.1016/j.jsb.2007.09.018

== Related software ==

== Related methods ==

== Comments ==

2008Bartesaghi Classification

2009-08-07T08:39:39Z

Jjfdez:

== Citation ==

Bartesaghi A, Sprechmann P, Liu J, Randall G, Sapiro G, Subramaniam S. Classification and 3D averaging with missing wedge correction in biological electron tomography. J Struct Biol. 2008 Jun;162(3):436-50.

== Abstract ==

Strategies for the determination of 3D structures of biological macromolecules using electron crystallography and single-particle electron microscopy utilize powerful tools for the averaging of information obtained from 2D projection images of structurally homogeneous specimens. In contrast, electron tomographic approaches have often been used to study the 3D structures of heterogeneous, one-of-a-kind objects such as whole cells where image-averaging strategies are not applicable. Complex entities such as cells and viruses, nevertheless, contain multiple copies of numerous macromolecules that can individually be subjected to 3D averaging. Here we present a complete framework for alignment, classification, and averaging of volumes derived by electron tomography that is computationally efficient and effectively accounts for the missing wedge that is inherent to limited-angle electron tomography. Modeling the missing data as a multiplying mask in reciprocal space we show that the effect of the missing wedge can be accounted for seamlessly in all alignment and classification operations. We solve the alignment problem using the convolution theorem in harmonic analysis, thus eliminating the need for approaches that require exhaustive angular search, and adopt an iterative approach to alignment and classification that does not require the use of external references. We demonstrate that our method can be successfully applied for 3D classification and averaging of phantom volumes as well as experimentally obtained tomograms of GroEL where the outcomes of the analysis can be quantitatively compared against the expected results.

== Keywords ==

Cryo-electron tomography; Missing wedge effect; Volume registration; Volume classification; Volume averaging

== Links ==

Article http://dx.doi.org/10.1016/j.jsb.2008.02.008

== Related software ==

== Related methods ==

== Comments ==

2008Forster Classification

2009-08-07T08:37:35Z

Jjfdez:

== Citation ==

Förster F, Pruggnaller S, Seybert A, Frangakis AS. Classification of cryo-electron sub-tomograms using constrained correlation. J Struct Biol. 2008 Mar;161(3):276-86.

== Abstract ==

Cryo-electron tomography (CET) is currently the only three-dimensional imaging technique capable of visualizing macromolecules in their cellular context at close-to-native conditions with a resolution in the nanometer range. An important component for the analysis of the data is their classification, which should discriminate among various macromolecules, conformational changes and interaction partners. Missing structure factors, typically in a wedge-shaped region in Fourier space if single-axis tilting is performed, hamper classification of cryo-electron tomographic data. Here, we describe a classification method for three-dimensional (3D) sub-tomograms extracted from cryo-electron tomograms, which takes the missing wedge into account and provides reliable results. The similarity of the individually aligned sub-tomograms is scored by constrained correlation. Subsequently, they are clustered based on their pairwise correlation values. In order to demonstrate the feasibility of this approach, we apply the proposed method to simulated tomographic data of the chaperone thermosome in different conformations. By comparison of the principal components of the resulting matrix we show that the proposed metric is significantly less prone to the orientation of the missing wedge compared to the unconstrained correlation. Moreover, we apply our classification method to an experimental dataset of GroEL with and without GroES, where we achieve a distinct discrimination between the putative GroEL and GroEL/GroES complexes.

== Keywords ==

Electron tomography; Classification; Correlation; Multivariate statistical analysis; k-Means

== Links ==

Article http://dx.doi.org/10.1016/j.jsb.2007.07.006

== Related software ==

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== Comments ==

2006Frank TomoBook

2009-08-06T17:57:42Z

Jjfdez:

== Citation ==

Electron Tomography. Methods for Three-Dimensional Visualization of Structures in the Cell, 2nd edition.
Frank, J. (Ed.). Springer, 2006. ISBN: 978-0387312347

== Links ==

http://www.springer.com/life+sci/book/978-0-387-31234-7

== Comments ==

2007McIntosh Book

2009-08-06T17:52:47Z

Jjfdez:

== Citation ==
Cellular Electron Microscopy. Edited by: J. Richard McIntosh. Methods in Cell Biology. Volume 79, Pages 1-850 (2007)

== Links ==
[http://www.sciencedirect.com/science?_ob=PublicationURL&_tockey=%23TOC%2318065%232007%23999209999%23645179%23FLA%23&_cdi=18065&_pubType=BS&view=c&_auth=y&_acct=C000048559&_version=1&_urlVersion=0&_userid=4224797&md5=24f79194fb113d20a4fc3c394e4af342 Book]

2007Forster Review

2009-08-06T17:47:34Z

Jjfdez:

== Citation ==
Forster F, Hegerl R. Structure Determination In Situ by Averaging of Tomograms. Methods Cell Biol. 2007;79:741-767.

== Abstract ==
Averaging single particles that have been extracted from cryoelectron tomograms is a powerful method for visualizing macromolecular complexes in situ. Cryoelectron tomography (CET) is uniquely suited to obtaining three-dimensional (3D) insights into pleiomorphic objects such as cells or organelles. Frozen-hydrated specimens provide excellent preservation of biological material, and thus a cryoelectron tomogram depicts a faithful image of complexes in situ. However, the resolution of CET is limited by the applicable electron dose; this limitation can be overcome for macromolecules that occur in identical copies within one or many tomograms by coherently averaging them. If the differently oriented and positioned particles are brought into precise register, their weak individual signals are amplified, resulting in an average that is of higher resolution. Here we report on the image processing that is needed to align the single particles to a common coordinate system, both in theory and in practice. Our method iteratively optimizes a scoring function that adopts its maximum value when all particles are in register; the scoring function is a cross-correlation function that accounts for the “missing-wedge effect,” currently the most prominent imaging artifact in CET. Structural characterization by CET and subsequent averaging can be particularly fruitful for unraveling the architecture of membrane-bound complexes.

== Keywords ==

== Links ==
Article: http://dx.doi.org/10.1016/S0091-679X(06)79029-X

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== Comments ==

2007Best Review

2009-08-06T17:47:10Z

Jjfdez:

== Citation ==
Best C, Nickell S, Baumeister W. Localization of protein complexes by pattern recognition. Methods Cell Biol. 2007;79:615-38.

== Abstract ==
As cryo-electron tomography of whole cells or cell sections approaches molecular resolution, it becomes feasible to locate protein complexes in cells by their distinctive three-dimensional (3D) structures alone, without the need of markers. This opens the way to creating a molecular map of the cellular proteome and its interactions under near-life conditions. However, the process requires sophisticated computational methods to create large libraries of molecular templates and search for them in cellular tomograms, taking into account the low signal-to-noise ratio and limited resolution of cryo-electron tomography (cryo-ET), as well as the problem of the missing wedge.

== Keywords ==

== Links ==
Article: http://dx.doi.org/10.1016/S0091-679X(06)79025-2

== Related software ==

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== Comments ==

2007Best Review

2009-08-06T17:41:33Z

Jjfdez:

== Citation ==
Best C, Nickell S, Baumeister W. Localization of protein complexes by pattern recognition. Methods Cell Biol. 2007;79:615-38.Click here to read

== Abstract ==
As cryo-electron tomography of whole cells or cell sections approaches molecular resolution, it becomes feasible to locate protein complexes in cells by their distinctive three-dimensional (3D) structures alone, without the need of markers. This opens the way to creating a molecular map of the cellular proteome and its interactions under near-life conditions. However, the process requires sophisticated computational methods to create large libraries of molecular templates and search for them in cellular tomograms, taking into account the low signal-to-noise ratio and limited resolution of cryo-electron tomography (cryo-ET), as well as the problem of the missing wedge.

== Keywords ==

== Links ==
Article: http://dx.doi.org/10.1016/S0091-679X(06)79025-2

== Related software ==

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== Comments ==

2003Jiang Bilateral

2009-08-06T17:36:42Z

Jjfdez:

== Citation ==
Jiang W, Baker ML, Wu Q, Bajaj C, Chiu W. Applications of a bilateral denoising filter in biological electron microscopy. J Struct Biol. 2003 Oct-Nov;144(1-2):114-22.

== Abstract ==
Due to the sensitivity of biological sample to the radiation damage, the low dose imaging conditions used for electron microscopy result in extremely noisy images. The processes of digitization, image alignment, and 3D reconstruction also introduce additional sources of noise in the final 3D structure. In this paper, we investigate the effectiveness of a previous termbilateralnext term denoising filter in various biological electron microscopy applications. In contrast to the conventional low pass filters, which inevitably smooth out both noise and structural features simultaneously, we found that previous termbilateralnext term filter holds a distinct advantage in being capable of effectively suppressing noise without blurring the high resolution details. In as much, we have applied this technique to individual micrographs, entire 3D reconstructions, segmented proteins, and tomographic reconstructions.

== Keywords ==

== Links ==
Article: http://dx.doi.org/10.1016/j.jsb.2003.09.028

== Related software ==

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== Comments ==

2008Fernandez HPCReview

2009-08-06T16:19:01Z

Jjfdez:

== Citation ==

Fernández, JJ. High performance computing in structural determination by electron cryomicroscopy. J.Struct.Biol. 164:1-6, 2008.

== Abstract ==

Computational advances have significantly contributed to the current role of electron cryomicroscopy (cryoEM) in structural biology. The needs for computational power are constantly growing with the increasing complexity of algorithms and the amount of data needed to push the resolution limits. High performance computing (HPC) is becoming paramount in cryoEM to cope with those computational needs. Since the nineties, different HPC strategies have been proposed for some specific problems in cryoEM and, in fact, some of them are already available in common software packages. Nevertheless, the literature is scattered in the areas of computer science and structural biology. In this communication, the HPC approaches devised for the computation-intensive tasks in cryoEM (single particles and tomography) are retrospectively reviewed and the future trends are discussed. Moreover, the HPC capabilities available in the most common cryoEM packages are surveyed, as an evidence of the importance of HPC in addressing the future challenges.

== Keywords ==

high performance computing, electron tomography, single particles

== Links ==

Article: http://dx.doi.org/10.1016/j.jsb.2008.07.005

== Related software ==

== Related methods ==

== Comments ==

2007Sandberg OrientationFields

2009-08-06T10:16:27Z

Jjfdez:

== Citation ==
Sandberg K, Brega M. Segmentation of thin structures in electron micrographs using orientation fields. J Struct Biol. 2007 Feb;157(2):403-15

== Abstract ==
In this paper, we introduce a new approach for segmenting thin structures in electron micrographs. We introduce two new transforms, the Line Filter Transform (LFT) and the Orientation Filter Transform (OFT). The LFT can be viewed as an alternative to anisotropic diffusion algorithms that is particularly useful for thin structures. The OFT utilizes geometrical information about the structure by measuring correlations of local orientations in the image. By combining these methods with a contour extraction and labeling method we construct a segmentation method for thin structures in 2D images. We discuss how the method can be applied slice-by-slice to electron tomograms and illustrate the process by constructing two models of membrane structures from cellular tomograms. The suggested method has the advantage of being relatively insensitive to non-uniform contrast and high-contrast features such as ribosomes.

== Keywords ==

== Links ==
Article: http://dx.doi.org/10.1016/j.jsb.2006.09.007

== Related software ==

== Related methods ==

== Comments ==

2007Heide median

2009-08-06T10:02:40Z

Jjfdez: 2007 Heide median moved to 2007Heide median

== Citation ==
van der Heide P, Xu XP, Marsh BJ, Hanein D, Volkmann N. Efficient automatic noise reduction of electron tomographic reconstructions based on iterative median filtering. J Struct Biol. 2007 158(2):196-204.

== Abstract ==
A simple, fast and efficient noise-reduction protocol for three-dimensional electron tomographic reconstructions of biological material is presented. The approach is based on iterative application of median filtering and shows promise for automatic noise reduction as a pre-processor for automated data analysis tools which aim at segmentation, feature extraction and pattern recognition. The application of this algorithm produces encouraging results for a wide variety of experimental and synthetic electron tomographic reconstructions.

== Keywords ==
Electron microscopy; Electron tomography; Cryo-microscopy; Noise reduction; Image processing; Automation

== Links ==
Article: http://dx.doi.org/10.1016/j.jsb.2006.10.030

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== Comments ==

2009Fernandez Beltrami

2009-08-06T10:01:49Z

Jjfdez:

== Citation ==
Fernandez JJ. TOMOBFLOW: feature-preserving noise filtering for electron tomography. BMC Bioinformatics. 2009 Jun 12;10:178.

== Abstract ==
BACKGROUND: Noise filtering techniques are needed in electron tomography to allow proper interpretation of datasets. The standard linear filtering techniques are characterized by a tradeoff between the amount of reduced noise and the blurring of the features of interest. On the other hand, sophisticated anisotropic nonlinear filtering techniques allow noise reduction with good preservation of structures. However, these techniques are computationally intensive and are difficult to be tuned to the problem at hand. RESULTS: TOMOBFLOW is a program for noise filtering with capabilities of preservation of biologically relevant information. It is an efficient implementation of the Beltrami flow, a nonlinear filtering method that locally tunes the strength of the smoothing according to an edge indicator based on geometry properties. The fact that this method does not have free parameters hard to be tuned makes TOMOBFLOW a user-friendly filtering program equipped with the power of diffusion-based filtering methods. Furthermore, TOMOBFLOW is provided with abilities to deal with different types and formats of images in order to make it useful for electron tomography in particular and bioimaging in general. CONCLUSION: TOMOBFLOW allows efficient noise filtering of bioimaging datasets with preservation of the features of interest, thereby yielding data better suited for post-processing, visualization and interpretation. It is available at the web site (http://www.ual.es/%7ejjfdez/SW/tomobflow.html).

== Keywords ==

== Links ==
Article: http://dx.doi.org/10.1186/1471-2105-10-178

== Related software ==
[http://www.ual.es/~jjfdez/SW/tomobflow.html TOMOBFLOW]
== Related methods ==

== Comments ==

2009Fernandez Beltrami

2009-08-06T10:01:17Z

Jjfdez:

2003Bajaj BoundarySegmentation

2009-08-06T09:58:46Z

Jjfdez:

== Citation ==
Bajaj C, Yu Z, Auer M. Volumetric feature extraction and visualization of tomographic molecular imaging. J Struct Biol. 2003 Oct-Nov;144(1-2):132-43.

== Abstract ==
Electron tomography is useful for studying large macromolecular complex within their cellular context. The associate problems include crowding and complexity. Data exploration and 3D visualization of complexes require rendering of tomograms as well as extraction of all features of interest. We present algorithms for fully automatic boundary segmentationnext term and skeletonization, and demonstrate their applications in feature extraction and visualization of cell and molecular tomographic imaging. We also introduce an interactive volumetric exploration and visualization tool (Volume Rover), which encapsulates implementations of the above volumetric image processing algorithms, and additionally uses efficient multi-resolution interactive geometry and volume rendering techniques for interactive visualization.

== Keywords ==

== Links ==
Article: http://dx.doi.org/10.1016/j.jsb.2003.09.037

== Related software ==

== Related methods ==

== Comments ==

2007Sandberg SegmentationReview

2009-08-06T09:53:28Z

Jjfdez:

== Citation ==
Sandberg K. Methods for image segmentation in cellular tomography. Methods Cell Biol. 2007;79:769-98

== Abstract ==
In this chapter, we discuss and illustrate some of the challenges for constructing robust and efficient segmentation methods for cellular tomography. We also discuss some approaches for evaluating the usability of segmentation methods and suggest a possible approach for quantifying the accuracy of segmentation algorithms. The chapter includes a review of several existing methods for denoising, contrast enhancement, and segmentation. We point out that some frequently suggested methods are often impractical for real data sets due to the computational complexity and difficulty in finding appropriate algorithm parameters. Furthermore, we claim that segmentation methods based only on intensity and contrast have problems in detecting thin, elongated structures. Instead, we propose using geometrical information, such as correlation among orientations, in order to detect membranes and microtubules. Finally, we outline a new orientation-based segmentation method and demonstrate this method on real tomograms.

== Keywords ==

== Links ==
Article: http://dx.doi.org/10.1016/S0091-679X(06)79030-6

== Related software ==

== Related methods ==

== Comments ==

2007Sandberg OrientationFields

2009-08-06T09:49:28Z

Jjfdez:

== Citation ==
Sandberg K, Brega M. Segmentation of thin structures in electron micrographs using orientation fields. J Struct Biol. 2007 Feb;157(2):403-15

== Abstract ==
In this paper, we introduce a new approach for segmenting thin structures in electron micrographs. We introduce two new transforms, the Line Filter Transform (LFT) and the Orientation Filter Transform (OFT). The LFT can be viewed as an alternative to anisotropic diffusion algorithms that is particularly useful for thin structures. The OFT utilizes geometrical information about the structure by measuring correlations of local orientations in the image. By combining these methods with a contour extraction and labeling method we construct a previous termsegmentationnext term method for thin structures in 2D images. We discuss how the method can be applied slice-by-slice to electron tomograms and illustrate the process by constructing two models of membrane structures from cellular tomograms. The suggested method has the advantage of being relatively insensitive to non-uniform contrast and high-contrast features such as ribosomes.

== Keywords ==

== Links ==
Article: http://dx.doi.org/10.1016/j.jsb.2006.09.007

== Related software ==

== Related methods ==

== Comments ==

2002Volkmann Watershed

2009-08-06T09:46:28Z

Jjfdez:

== Citation ==
Volkmann N. A novel three-dimensional variant of the watershed transform for segmentation of electron density maps. J Struct Biol. 2002 Apr-May;138(1-2):123-9.

== Abstract ==
Electron density maps at moderate resolution are often difficult to interpret due to the lack of recognizable features. This is especially true for electron tomograms that suffer in addition to the resolution limitation from low signal-to-noise ratios. Reliable previous termsegmentationnext term of such maps into smaller, manageable units can greatly facilitate interpretation. Here, we present a previous termsegmentationnext term approach targeting three-dimensional electron density maps derived by electron microscopy. The approach consists of a novel three-dimensional variant of the immersion-based watershed algorithm. We tested the algorithm on calculated data and applied it to a wide variety of electron density maps ranging from reconstructions of single macromolecules to tomograms of subcellular structures. The results indicate that the algorithm is reliable, efficient, accurate, and applicable to a wide variety of biological problems.

== Keywords ==

== Links ==
Article: http://dx.doi.org/10.1016/S1047-8477(02)00009-6

== Related software ==

== Related methods ==

== Comments ==

2008Garduno FuzzySegmentation

2009-08-06T09:44:23Z

Jjfdez:

== Citation ==
Garduño E, Wong-Barnum M, Volkmann N, Ellisman MH. Segmentation of electron tomographic data sets using fuzzy set theory principles. J Struct Biol. 2008 Jun;162(3):368-79.

== Abstract ==
In electron tomography the reconstructed density function is typically corrupted by noise and artifacts. Under those conditions, separating the meaningful regions of the reconstructed density function is not trivial. Despite development efforts that specifically target electron tomography manual previous termsegmentationnext term continues to be the preferred method. Based on previous good experiences using a previous termsegmentationnext term based on fuzzy logic principles (fuzzy previous termsegmentationnext term) where the reconstructed density functions also have low signal-to-noise ratio, we applied it to electron tomographic reconstructions. We demonstrate the usefulness of the fuzzy previous termsegmentationnext term algorithm evaluating it within the limits of segmenting electron tomograms of selectively stained, plastic embedded spiny dendrites. The results produced by the fuzzy previous termsegmentationnext term algorithm within the framework presented are encouraging.

== Keywords ==

== Links ==
Article: http://dx.doi.org/10.1016/j.jsb.2008.01.017

== Related software ==

== Related methods ==

== Comments ==

2009Lebbink TemplateMatching2

2009-08-06T09:40:18Z

Jjfdez:

== Citation ==

Lebbink MN, van Donselaar E, Humbel BM, Hertzberger LO, Post JA, Verkleij AJ. Induced membrane domains as visualized by electron tomography and template matching. J Struct Biol. 2009 May;166(2):156-61.

== Abstract ==
Membranes play a crucial role in many cellular processes, and it is therefore not surprising that many electron tomographic studies in life sciences concern membranous structures. While these tomographic studies provide many new insights into membrane connections and continuities in three dimensions, they are mostly limited to a macro-morphological level. In this paper, we demonstrate that by combining electron tomography and three-dimensional template matching we are able to investigate membrane morphology at a new level: membrane domains in three dimensions. To test this, temperature induced lipid phase separation in the biological model system of the Escherichia coli bacteria was used. We compared the inner (containing phospholipids) and outer (containing lipopolysaccharides) leaflet of the E. coli outer membrane at both 37 and -20 degrees C, and could visualize how these leaflets react differently to temperature shifts. These findings can be explained by the physico-chemical nature of the building blocks and are in line with earlier published data. This study shows that the combination of electron tomography and template matching is robust enough to visualize membrane domains that are beyond the perception of manual annotation.

== Keywords ==

== Links ==
Article: http://dx.doi.org/10.1016/j.jsb.2009.01.006

== Related software ==

== Related methods ==

2009Lebbink TemplateMatching2

2009-08-06T09:39:18Z

Jjfdez:

== Citation ==

Lebbink MN, van Donselaar E, Humbel BM, Hertzberger LO, Post JA, Verkleij AJ. Induced membrane domains as visualized by electron tomography and template matching. J Struct Biol. 2009 May;166(2):156-61.

== Abstract ==

Three-dimensional electron microscopy (3DEM) has made significant contributions to structural biology. To accomplish this feat, many image-processing software packages were developed by various laboratories. The independent development of methods naturally implied the adoption of dissimilar conventions-penalizing users who want to take advantage of the wealth of algorithms from different packages. In addition, a public repository of 3DEM research results, the EM Data Bank, is now established. In an era where information exchange is important, standardizing conventions is a necessity. The 3DEM field requires a consistent set of conventions. We propose a set of common conventions named the "3DEM Image Conventions." They are designed as a standardized approach to image interpretation and presentation. In this regard, the conventions serve as a first step on which to build data-exchange solutions among existing software packages and as a vehicle for homogenous data representation in data archives, such as the EM Data Bank.

== Keywords ==

Conventions, software interoperability

== Links ==

2007Lebbink TemplateMatching

2009-08-06T09:35:53Z

Jjfdez:

== Citation ==
Lebbink MN, Geerts WJ, van der Krift TP, Bouwhuis M, Hertzberger LO, Verkleij AJ, Koster AJ. Template matching as a tool for annotation of tomograms of stained biological structures. J Struct Biol. 2007 Jun;158(3):327-35.

== Abstract ==
In recent years, electron tomography has improved our three-dimensional (3D) insight in the structural architecture of cells and organelles. For studies that involve the 3D imaging of stained sections, manual annotation of tomographic data has been an important method to help understand the overall 3D morphology of cellular compartments. Here, we postulate that template matching can provide a tool for more objective annotation and contouring of cellular structures. Also, this technique can extract information hitherto unharvested in tomographic studies. To evaluate the performance of template matching on tomograms of stained sections, we generated several templates representing a piece of microtubule or patches of membranes of different staining-thicknesses. These templates were matched to tomograms of stained electron microscopy sections. Both microtubules and ER-Golgi membranes could be detected using this method. By matching cuboids of different thicknesses, we were able to distinguish between coated and non-coated endosomal membrane-domains. Finally, heterogeneity in staining-thickness of endosomes could be observed. Template matching can be a useful addition to existing annotation-methods, and provide additional insights in cellular architecture.

== Keywords ==

== Links ==
Article: http://dx.doi.org/10.1016/j.jsb.2006.12.001

== Related software ==

== Related methods ==

== Comments ==

2006Radermacher WBP

2009-06-02T13:57:03Z

Jjfdez: 2006Radermacher WBP moved to 2007Radermacher WBP

#REDIRECT [[2007Radermacher WBP]]