CTBoneSegmenter.json

{
  "name": "CT Bone Segmenter",
  "number_of_inputs": 1,
  "task": "Segmentation.",
  "organ": "Chest",
  "modality": "CT",
  "train_test_data_details": "The model is trained on CT data reconstructed with a variety of reconstruction kernels with and without contrast agent added.",
  "briefdescription": "A bone segmentation plugin for chest CT scans developed and trained by 4Quant using a modified UNET algorithm",
  "detaileddescription": "For more details visit http://4quant.com/Bone-Segmenter",
  "version": "1.0",
  "docker":
    {
    "dockerhub_repository": "4quant/bone-segmenter-cpu:v1",
    "digest": "sha256:ccf3ebcca020f10873c76fcdacc73be766180184540d9f164628be1a9e29cdb0",
    "size": "3.6 GB"
    }
  ,
  "training":
    {
      "number of subjects": 140
    }
  ,
  "test":
    {
      "number of subjects": 30,
      "Accuracy": 0.772,
      "Metric": "Dice Similarity"
    }
  ,
  "pixel_types": "BasicPixelIDTypeList",
  "vector_pixel_types_by_component": "VectorPixelIDTypeList",
  "members": [
    {
      "name": "InputVolume",
      "type": "volume",
      "iotype": "input",
      "voltype": "ScalarVolume",
      "default": "std::vector<unsigned int>(3, 64)",
      "itk_type": "typename FilterType::SizeType"
    },
    {
      "name": "OutputLabel",
      "type": "volume",
      "iotype": "output",
      "voltype": "LabelMap",
      "default": "std::vector<unsigned int>(3, 64)",
      "itk_type": "typename FilterType::SizeType"
    }
]
}