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Item _em_3d_reconstruction.details

Description

    General details on the 3d recontruction

Category

Item Examples

Example 1:

   Orientation determination using the random-conical data 
    collection method. This method uses a defined geometry in 
    the data collection, and is able to find the handedness of 
    the structure unambiguously. Each specimen field is imaged 
    twice, once tilted, once untilted. Particles are selected 
    simultaneously from both untilted- and tilted-specimen fields, 
    using a special interactive particle-selection program that is 
    able to "predict" the location of a particle in the tilted-specimen 
    field when its counterpart has been selected in the untilted field. 
    From the untilted-specimen particle data set, all particles are 
    selected that exhibit the same view. This can be done by using 
    alignment followed by classification. The corresponding 
    tilted-specimen data subset can be used to compute a reconstruction:
    the orientations of the tilted-particle projections lie on a cone 
    with fixed angle (the tilt angle) and random azimuths (the 
    in-plane angles found in the alignment of the untilted particle set).

1

Example 2:

   Orientation determination using common lines (a.k.a. 
    "angular reconstitution"). This method is based on the fact that 
    in Fourier space any two projections intersect along a central line 
    ("the common line"). Hence, in principle, the relative orientations 
    between three projections can be determined - except that the 
    handedness of the constellation is ambiguous. Because of the low 
    signal-to-noise ratio of raw particle images, averages of projections 
    falling into roughly the same orientation must be used. Since the 
    procedure leads to solutions presenting local minima, it must be 
    repeated several times to find solutions that form a cluster, 
    presumably around the global minimum. Such clustering of solutions 
    can be detected by multivariate statistical analysis of the resulting 
    3D maps. Two clusters are expected, one for each enantiomorph. 
    After initial structure is obtained, it should be further refined 
    using 3D projection matching strategy described next. 

2

Example 3:

   Orientation determination by 3D projection matching. Here the 
    existing 3D map is projected in many orientations on a regular 
    angular grid, and the resulting projections that are compared, 
    one by one, with each of the experimental projections. This comparison 
    (by cross-correlation ) yields a refined set of Eulerian angles , 
    with which a refined reconstruction can be computed using one 
    of the possible reconstruction techniques. This procedure requires
    iteration until the angles for each projection stabilize. 

3

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