CustusX  2019.06.06-dev+develop.3b92
An IGT application
Standard Filters

Overview

Standard filters.

Dilation Filter

This filter dilates a binary volume with a given radius in mm.

The dilation is performed using a ball structuring element.

Contour Filter

Find the surface of a binary volume using marching cubes. When you adjust the treshold, you will see a preview of the filter on the selected input volume.

  • Optional: Reduce input volume by a factor of 2 in each direction = 1/8 of original volume size
  • Marching Cubes contouring
  • Optional Windowed Sinc smoothing
  • Decimation of triangles
  • Optional preserve mesh topology
  • Number of iterations in smoothing filter. Higher number = more smoothing
  • Band pass width in smoothing filter. Smaller number = more smoothing

Resample Image Filter

Resample the volume into the space of the reference volume. Also crop to the same volume.

Smoothing Image Filter

Wrapper for a itk::SmoothingRecursiveGaussianImageFilter.

Computes the smoothing of an image by convolution with the Gaussian kernels implemented as IIR filters. This filter is implemented using the recursive gaussian filters.

Binary Threshold Image Filter

Segment out areas from the selected image using a threshold.

This filter produces an output image whose pixels are either one of two values ( OutsideValue or InsideValue ), depending on whether the corresponding input image pixels lie between the two thresholds ( LowerThreshold and UpperThreshold ). Values equal to either threshold is considered to be between the thresholds.

Centerline Filter

Wrapper for a itk::BinaryThinningImageFilter3D.

This filter computes one-pixel-wide skeleton of a 3D input image.

This class is parametrized over the type of the input image and the type of the output image.

The input is assumed to be a binary image. All non-zero valued voxels are set to 1 internally to simplify the computation. The filter will produce a skeleton of the object. The output background values are 0, and the foreground values are 1.

A 26-neighbourhood configuration is used for the foreground and a 6-neighbourhood configuration for the background. Thinning is performed symmetrically in order to guarantee that the skeleton lies medial within the object.

This filter is a parallel thinning algorithm and is an implementation of the algorithm described in:

T.C. Lee, R.L. Kashyap, and C.N. Chu.
Building skeleton models via 3-D medial surface/axis thinning algorithms.
Computer Vision, Graphics, and Image Processing, 56(6):462--478, 1994.