Software Open Access

elasticdeform: Elastic deformations for N-dimensional images

Gijs van Tulder


JSON Export

{
  "files": [
    {
      "links": {
        "self": "https://zenodo.org/api/files/53f5fc64-0783-4ff3-ae46-ec920d5f5541/gvtulder/elasticdeform-v0.4.9.zip"
      }, 
      "checksum": "md5:41a6d8a909d057b805eb88c013513995", 
      "bucket": "53f5fc64-0783-4ff3-ae46-ec920d5f5541", 
      "key": "gvtulder/elasticdeform-v0.4.9.zip", 
      "type": "zip", 
      "size": 125390
    }
  ], 
  "owners": [
    199805
  ], 
  "doi": "10.5281/zenodo.4569691", 
  "stats": {
    "version_unique_downloads": 6.0, 
    "unique_views": 124.0, 
    "views": 158.0, 
    "version_views": 189.0, 
    "unique_downloads": 5.0, 
    "version_unique_views": 139.0, 
    "volume": 752340.0, 
    "version_downloads": 7.0, 
    "downloads": 6.0, 
    "version_volume": 877607.0
  }, 
  "links": {
    "doi": "https://doi.org/10.5281/zenodo.4569691", 
    "conceptdoi": "https://doi.org/10.5281/zenodo.4563333", 
    "bucket": "https://zenodo.org/api/files/53f5fc64-0783-4ff3-ae46-ec920d5f5541", 
    "conceptbadge": "https://zenodo.org/badge/doi/10.5281/zenodo.4563333.svg", 
    "html": "https://zenodo.org/record/4569691", 
    "latest_html": "https://zenodo.org/record/4569691", 
    "badge": "https://zenodo.org/badge/doi/10.5281/zenodo.4569691.svg", 
    "latest": "https://zenodo.org/api/records/4569691"
  }, 
  "conceptdoi": "10.5281/zenodo.4563333", 
  "created": "2021-03-01T11:25:46.172568+00:00", 
  "updated": "2021-03-09T21:37:25.746151+00:00", 
  "conceptrecid": "4563333", 
  "revision": 5, 
  "id": 4569691, 
  "metadata": {
    "access_right_category": "success", 
    "doi": "10.5281/zenodo.4569691", 
    "description": "<p>This library implements elastic grid-based deformations for N-dimensional images.</p>\n\n<p>The elastic deformation approach is described in</p>\n\n<ul>\n\t<li>Ronneberger, Fischer, and Brox, &quot;U-Net: Convolutional Networks for Biomedical Image Segmentation&quot; (<a href=\"https://arxiv.org/abs/1505.04597\">https://arxiv.org/abs/1505.04597</a>)</li>\n\t<li>&Ccedil;i&ccedil;ek et al., &quot;3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation&quot; (<a href=\"https://arxiv.org/abs/1606.06650\">https://arxiv.org/abs/1606.06650</a>)</li>\n</ul>\n\n<p>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.</p>\n\n<p>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&nbsp;<code>elasticdeform.tf</code>.</p>\n\n<p>See <a href=\"https://github.com/gvtulder/elasticdeform\">https://github.com/gvtulder/elasticdeform</a></p>", 
    "license": {
      "id": "other-open"
    }, 
    "title": "elasticdeform: Elastic deformations for N-dimensional images", 
    "relations": {
      "version": [
        {
          "count": 2, 
          "index": 1, 
          "parent": {
            "pid_type": "recid", 
            "pid_value": "4563333"
          }, 
          "is_last": true, 
          "last_child": {
            "pid_type": "recid", 
            "pid_value": "4569691"
          }
        }
      ]
    }, 
    "version": "v0.4.9", 
    "publication_date": "2021-03-01", 
    "creators": [
      {
        "orcid": "0000-0003-1635-5423", 
        "name": "Gijs van Tulder"
      }
    ], 
    "access_right": "open", 
    "resource_type": {
      "type": "software", 
      "title": "Software"
    }, 
    "related_identifiers": [
      {
        "scheme": "url", 
        "identifier": "https://github.com/gvtulder/elasticdeform/tree/v0.4.9", 
        "relation": "isSupplementTo"
      }, 
      {
        "scheme": "doi", 
        "identifier": "10.5281/zenodo.4563333", 
        "relation": "isVersionOf"
      }
    ]
  }
}
189
7
views
downloads
All versions This version
Views 189158
Downloads 76
Data volume 877.6 kB752.3 kB
Unique views 139124
Unique downloads 65

Share

Cite as