ThesisInferenceServer/models.json at main · trainlab/ThesisInferenceServer · GitHub

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[
    {
      "id": 1,
      "title": "CT-to-PET (CL_ff)",
      "description": "Converts CT scans to synthetic PET images. Trained with curriculum learning with a forgetting factor",
      "inputModality": "CT",
      "outputModality": "PET",
      "region": "Total Body",
      "modelPath": "CL_ff_0.8_v2",
      "networkName": "BEST_final_400"
    },
    {
      "id": 2,
      "title": "CT-to-PET (Total Body)",
      "description": "Converts full-body CT scans to PET.",
      "inputModality": "CT",
      "outputModality": "PET",
      "region": "Total Body",
      "modelPath": "Test_switch",
      "networkName": "BEST_final_200"
    },
    {
      "id": 3,
      "title": "CT-to-PET (Curriculum learning)",
      "description": "Converts full-body CT scans to PET. Trained with a curriculum learning strategy",
      "inputModality": "CT",
      "outputModality": "PET",
      "region": "Total Body",
      "modelPath": "CL_baseline",
      "networkName": "BEST_final_400"
    }
    ,
    {
      "id": 4,
      "title": "CT-to-PET (CL_sampling)",
      "description": "Converts full-body CT scans to PET. Trained with a sampling strategy",
      "inputModality": "CT",
      "outputModality": "PET",
      "region": "Total Body",
      "modelPath": "CL_sampling",
      "networkName": "BEST_final_400"
    }
  ]