VoCentering

Summary

VoCentering

Process category

Brief description

Computational demand

for typical tomography data

(low, medium, high)

Comment(s)

Reference(s)

Common alternative process(es)

filter

To find an optimal value of CoR automatically.

High

Since the computational cost of this auto-centring process is high, it is normally applied to a small but representative subset of data (this can most conveniently be done with the aid of the preview parameter of this process).
Any reconstructor process included in a process chain after VoCentering will have its centre_of_rotation parameter automatically set to the value determined by the auto-centring process.
VoCentering should normally be included after a ring-artefact suppression process (such as, e.g. RemoveAllRings), but before any low-pass process such as PaganinFilter or FresnelFilter.

Reliable method for calculating the center of rotation in parallel-beam tomography

VoCenteringIterative

Parameters

Brief description

Savu Configurator command

>>> disp -avv

-------------------------------------------------------------------------------------
 1) VoCentering(savu.plugins.centering.vo_centering)                                 
  A plugin to find the center of rotation per frame                                  
    1)                preview : []
    A slice list of required frames (sinograms) to use in the calulation of the
    centre of rotation (this will not reduce the data size for subsequent plugins).
    2)            start_pixel : None
    The approximate centre. If value is None, take the value from .nxs file else set
    to image centre.
    3)            search_area : (-50, 50)
    Search area from horizontal approximate centre of the image.
    4)            in_datasets : []
    Create a list of the dataset(s) to process.
    5)          search_radius : 6
    Use for fine searching.
    6)                  ratio : 0.5
    The ratio between the size of object and FOV of the camera.
    7)           out_datasets : ['cor_raw', 'cor_fit']
    The default names.
    8)   datasets_to_populate : []
    A list of datasets which require this information.
    9)               row_drop : 20
    Drop lines around vertical center of the mask.
   10)                   step : 0.5
    Step of fine searching.
-------------------------------------------------------------------------------------

>>>

Additional notes

For basic information on this process, please use the disp -av (or disp -avv or disp -v[v] <process index>) command in Savu Configurator (see above). The table below is intended to provide some additional notes on a number of selected topics:

Item	Parameter name	Parameter format	Example(s)		Comment(s)
Item	Parameter name	Parameter format	Parameter value	Effect	Comment(s)
1	preview				Note that the *preview* parameter has a nested-cumulative behaviour, i. e. if one specifies VoCentering's *preview* parameter together with NxtomoLoader's *preview* parameter, then VoCentering will effectively be selecting a subset from NxtomoLoader's own subset (rather than the entire dataset). Note also that VoCentering's subset needs to be specified by indices referring to NxtomoLoader's own subset (rather than the entire dataset). For instance, one must set VoCentering's *preview* parameter to [:, 0, :] in order to select the initial slice of any dataset previously loaded by NxtomoLoader, which may, for example, be the [:, 123:456, :] subset of (456-123=333 slices of) the entire dataset. If you use any parameter tuning in one (or more) process(es) preceding VoCentering, then the latter will automatically receive (from the immediately preceding process) a dataset of order higher than 3. In this case, if you leave VoCentering's *preview* parameter at its default value (i.e. [ ]), then VoCentering will have too process the entire rank-N (N>3) dataset, which is hardly ever desired. To avoid this waste of resources, you should specify VoCentering's *preview* parameter to be a desired, reasonably-sized rank-3 slice of the incoming rank-N dataset. For instance, if you have generated a dataset of shape (D, img_W, img_L, T) by subjecting the original (D, img_W, img_L) data to a single parameter-tuning operation, then your new, parameter-tuned rank-4 dataset needs to be sliced in the last dimension (corresponding to T), e. g. one can use the [:, mid, :, 0] slice of this rank-4 dataset to select its rank-3 subset containing the middle sinogram that was created with the initial value of the tuning parameter.
2	start_pixel				An initial estimate for the pixel coordinate of an optimal CoR.
3	search_area				If the value of the *search_area* parameter is set to the default interval of (-50, 50), then VoCentering attempts to search for an optimal value of CoR in the (*start_pixel* - 50, *start_pixel* + 50) interval (if the user-specified value of *start_pixel* is None, then img_W/2 (or a value found in /entry1/tomo_entry/instrument/detector/x_rotation_axis_pixel_position) is used instead). For some datasets, this default, 100-pixel-wide range of search may not be sufficiently large to include an optimal value of CoR. Therefore, if the value of CoR determined by VoCentering is found to coincide with one of the search-interval limits (i. e. either start_pixel - 50 or *start_pixel* + 50), then this value of CoR may not necessarily be optimal, and one should re-run VoCentering with a larger value of the *search_area* parameter to confirm this result.
4	in_datasets
5	search_radius
6	ratio
7	out_datasets
8	datasets_to_populate
9	row_drop
10	step				Floating-point or integer value in pixel units.

Usage

TBC.

Tomography Reconstruction

VoCentering

Analytics

Summary

Parameters

Brief description

Additional notes

Usage

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