Isolated Connected CLP

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Isolated Connected Threshold Segmentation

General Information

  • Type: CLP
  • Category: Segmentation
  • Author: Xavi Planes
  • Contributor: Xavi Planes
  • Contact: xavier.planes@upf.edu
  • Description: Label pixels that are connected to one set of seeds but not another. IsolatedConnectedImageFilter finds the optimal threshold to separate two regions. It has two modes, one to separate dark regions surrounded by bright regions by automatically finding a minimum isolating upper threshold, and another to separate bright regions surrounded by dark regions by automatically finding a maximum lower isolating threshold. The mode can be chosen by setting FindUpperThresholdOn()/Off(). Read More....

Usage

Parameters

Label Type Flag / Index Default value / Channel Description
Parameters to denoise the image prior to segmenting
Smoothing iterations integer --smoothingIterations 5 Number of smoothing iterations
Timestep double --timestep 0.0625 Timestep for curvature flow
Parameters to prescribe the region growing
Lower double --lower 0 Set Upper and Lower Threshold inputs as values
Upper double --upper 1000 Set Upper and Lower Threshold inputs as values
Output Label Value integer --labelvalue 2 The integer value (0-255) to use for the segmentation results. This will determine the color of the segmentation that will be generated by the Region growing algorithm
Seeds point coordinateSystem="ras" multiple="true" --seed 0,0,0 Seed point(s) for region growing
IO
Input Volume image index 0 input Input volume to be filtered
Output Volume image index 1 output Output Volume

Examples

Sample Data:Atrial Fibrillation

In this example, the heart is segmented using two set of landmarks: the bright ones and the dark ones, while the filter find the optimal lower threshold:

Isolated Connected Threshold Segmentation

Development

Source code: C++ Source code and XML description

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