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elasticdeform: Elastic deformations for N-dimensional images

Gijs van Tulder

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<oai_dc:dc xmlns:dc="" xmlns:oai_dc="" xmlns:xsi="" xsi:schemaLocation="">
  <dc:creator>Gijs van Tulder</dc:creator>
  <dc:description>This library implements elastic grid-based deformations for N-dimensional images.

The elastic deformation approach is described in

	Ronneberger, Fischer, and Brox, "U-Net: Convolutional Networks for Biomedical Image Segmentation" (
	Çiçek et al., "3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation" (

The procedure generates a coarse displacement grid with a random displacement for each grid point. This grid is then interpolated to compute a displacement for each pixel in the input image. The input image is then deformed using the displacement vectors and a spline interpolation.

In addition to the normal, forward deformation, this package also provides a function that can backpropagate the gradient through the deformation. This makes it possible to use the deformation as a layer in a convolutional neural network. For convenience, a TensorFlow wrapper is provided in

  <dc:title>elasticdeform: Elastic deformations for N-dimensional images</dc:title>
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