LymphNodeSegmenter.json

{
  "name": "Lymph Node Segmentation",
  "number_of_inputs": 1,
  "task": "Segmentation.",
  "organ": "Mediastinal Lymph Nodes",
  "modality": "CT",
  "train_test_data_details": "Models were trained using TCIA CT Lymph Nodes dataset.",
  "briefdescription": ".",
  "detaileddescription": "",
  "website": "",
  "citation": "",
  "version": "0.1",
  "docker": {
    "dockerhub_repository": "deepinfer/lnq",
    "digest": "sha256:ed7e56549b5bcd630295874673bde2cdc271f772335c0b145b4cac42bafa62d4",
    "size": "3.7 GB"
  },
  "model_name": "lnq_segmentation_med",
  "data_path": "/data",
  "members": [
    {
      "name": "InferenceType",
      "type": "enum",
      "enum": [
        "Ensemble 10",
        "Ensemble 50",
        "Single"
      ],
      "detaileddescriptionSet": "Ensemble models are more accurate. Single models are less accurate.\n",
      "iotype": "parameter"
    },
    {
      "name": "InputVolume",
      "type": "volume",
      "iotype": "input",
      "voltype": "ScalarVolume",
      "detaileddescriptionSet": "Mediastinal CT scan.\n",
      "default": "std::vector<unsigned int>(3, 64)",
      "itk_type": "typename FilterType::SizeType"
    },
    {
      "name": "InputFiducialList",
      "type": "point_vec",
      "iotype": "input",
      "detaileddescriptionSet": "Input fiducial list for centers of 64 mm^3 cubes.\n"
    },
    {
      "name": "OutputProbmap",
      "type": "volume",
      "iotype": "output",
      "voltype": "ScalarVolume",
      "detaileddescriptionSet": "Output probability map for the segmentation results.\n",
      "default": "std::vector<unsigned int>(3, 64)",
      "itk_type": "typename FilterType::SizeType"
    },
    {
      "name": "OutputLabel",
      "type": "volume",
      "iotype": "output",
      "voltype": "LabelMap",
      "detaileddescriptionSet": "Output labelmap for the segmentation results.\n",
      "default": "std::vector<unsigned int>(3, 64)",
      "itk_type": "typename FilterType::SizeType"
    }
  ]
}