Projection Shift

Description

Horizontal and vertical shift are calculated using a chosen method and added to the metadata. The vertical and horizontal shifts can be corrected using the ProjectionVerticalAlignment and SinogramAlignment (in ‘shift’ mode) plugins respectively. Method: Uses either skimage template_matching or orb feature tracking plus robust ransac matching to calculate the translation between different combinations of 10 consecutive projection images. A least squares solution to the shift values between images is calculated and returned for the middle 8 images.

• Plugin documention and guidelines on use

Parameters

in_datasets:
    visibility: datasets
    dtype: "[list[],list[str]]"
    description:
        summary: A list of the dataset(s) to process.
        verbose: A list of strings, where each string gives the name of a dataset that was either specified by a loader plugin or created as output to a previous plugin.  The length of the list is the number of input datasets requested by the plugin.  If there is only one dataset and the list is left empty it will default to that dataset.
    default: "[]"

out_datasets:
    visibility: datasets
    dtype: "[list[],list[str]]"
    description: Set the output dataset name
    default: "['proj_shift']"

method:
    visibility: intermediate
    dtype: str
    description: Method used to calculate the shift between images.
    default: orb_ransac
    options: "['template_matching', 'orb_ransac']"

template:
    visibility: basic
    dtype: "[list[str],None]"
    description: "Position of the template to match (required) e.g. [300:500, 300:500]."
    default: None

threshold:
    visibility: intermediate
    dtype: "[list[float,float],None]"
    description: "e.g. [a, b] will set all values above a to b."
    default: None

n_keypoints:
    dependency:
        method: orb_ransac
    visibility: intermediate
    dtype: int
    description: Number of keypoints to use in ORB feature detector.
    default: "20"

Key

visibility: The visibility level of the parameter
dtype: The type of data
description: A short explanation of the parameter
default: The default value
options: A list of permitted values
dependency: The name of the parameter and value which this parameter depends upon
range: A guide for the range of the parameter

Citations

No citations

API

class ProjectionShift

get_max_frames()

nOutput_datasets()

The number of datasets created by the plugin

Returns

Number of output datasets

post_process()

This method is called after the process function in the pipeline framework as a post-processing step. All processes will have finished performing the main processing at this stage.

Parameters

exp (experiment class instance) – An experiment object, holding input and output datasets

pre_process()

This method is called immediately after base_pre_process().

process_frames(data)

This method is called after the plugin has been created by the pipeline framework and forms the main processing step

Parameters

data (list(np.array)) – A list of numpy arrays for each input dataset.

set_filter_padding(in_data, out_data)

Should be overridden to define how wide the frame should be for each input data set

setup()

This method is first to be called after the plugin has been created. It determines input/output datasets and plugin specific dataset information such as the pattern (e.g. sinogram/projection).