{
  "presets": [
    {
      "display_name": "Generic Rigid + BSpline",
      "parameter_maps":  [
          "Parameters_Rigid.txt",
          "Parameters_BSpline.txt"
      ],
      "models": [],
      "preprocess_function": "",
      "iterations": 3000,
      "short_description": "Two-stage registration: rigid alignment followed by BSpline refinement.",
      "description": "A combined registration strategy: first a rigid Euler transform corrects global misalignment, then a BSpline model captures localized anatomical deformations. Both stages use a multi-resolution pyramid, mutual information, and stochastic optimization for robust performance across a wide range of multimodal imaging scenarios."
    },
    {
      "display_name": "Generic Rigid",
      "parameter_maps":  [
          "Parameters_Rigid.txt"
      ],
      "models": [],
      "preprocess_function": "",
      "iterations": 1000,
      "short_description": "Rigid registration using mutual information and a multi-resolution pyramid.",
      "description": "This preset performs rigid alignment using an Euler transform optimized with Adaptive Stochastic Gradient Descent. It uses a 4-level multi-resolution strategy and Mattes mutual information as similarity metric. Initial alignment based on image centers are enabled to ensure robust convergence for multimodal images."
    },
    {
      "display_name": "IMPACT BSpline M730",
      "parameter_maps": [
          "ParameterMap_Recommended.txt"
      ],
      "models": [
          "VBoussot/impact-torchscript-models:TS/M730_2_Layers.pt"
      ],
      "preprocess_function": "Preprocess:standardize_MRI",
      "iterations": 1900,
      "short_description": "IMPACT-based multimodal BSpline registration with deep semantic features (M730)",
      "description": "A deformable BSpline registration using the IMPACT metric to align semantic features extracted from pretrained models (MIND + M730). The method uses 4 resolution levels."  
    }
  ]
}