Region Grow

Description

Fast 2D segmentation by evolving the user-given mask, the initialised mask should be set in the central part of the object to be segmented.

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: The default names
    default: "['MASK_RG_EVOLVED']"

threshold:
    visibility: basic
    dtype: float
    description: parameter to control mask propagation.
    default: "1.0"

method:
    visibility: intermediate
    dtype: str
    description: a method to collect statistics from the given mask (mean, median, value).
    default: mean

iterations:
    visibility: basic
    dtype: int
    description: number of iterations.
    default: "500"

connectivity:
    visibility: intermediate
    dtype: int
    description: the connectivity of the local neighbourhood, choose 4 or 8.
    default: "4"
    options: "[4, 8]"

pattern:
    visibility: basic
    dtype: str
    description: pattern to apply this to.
    default: VOLUME_YZ

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 RegionGrow

get_max_frames()

nInput_datasets()

The number of datasets required as input to the plugin

Returns

Number of input datasets

nOutput_datasets()

The number of datasets created by the plugin

Returns

Number of 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.

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).