Merge tag 'v1.8.7' into plan/main-presets

v1.8.7

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ConvexAdam_Coarse/Prediction.yml

@@ -5,24 +5,12 @@ Predictor:
       models:
         '0':
           ref: VBoussot/impact-torchscript-models:MIND/R1D2_3D.pt
-          voxel_size:
-          - 3.0
-          - 3.0
-          - 3.0
           layers_mask: '1'
-          layers_weight: 1.0
-          pca: 0
-          distance: L1
-      overlap: 2
+          layers_weight:
+          - 1.0
       mixed_precision: false
       grid_spacing: 6
       displacement_half_width: 4
-      iterations: 80
-      learning_rate: 1.0
-      regularization_weight: 1.25
-      grid_shrink: 2
-      control_grid_smoothing: 3
-      subset_features: []
       linear: true
       linear_iterations: 200
       seed: 42
@@ -79,10 +67,15 @@ Predictor:
             prob: 1
         nb: 2
     Patch:
-      patch_size: [0, 0, 0]
+      patch_size:
+      - 0
+      - 0
+      - 0
       overlap: 20%
       pad_value: None
       extend_slice: 0
+      mode: resample
+      max_voxels: None
     subset: None
     dataset_filenames:
     - ./Dataset/:mha

ConvexAdam_Coarse/app.json

@@ -85,5 +85,17 @@
                 }
             }
         }
-    }
+    },
+    "vram_bytes_per_voxel": 350,
+    "tiling": {
+        "global": "Prediction.yml"
+    },
+    "ram_bytes_per_voxel": 800,
+    "model_files": [
+        {
+            "repo_id": "VBoussot/impact-torchscript-models",
+            "revision": "47ffad660e67cebbac8d74aecf0fa181c5dac042",
+            "filename": "MIND/R1D2_3D.pt"
+        }
+    ]
 }

ConvexAdam_Coarse/requirements.txt

@@ -1,2 +1,2 @@
-itk-impact>=0.1.1
+itk-impact==0.1.6
 impact_reg_konfai>=1.7.0

ConvexAdam_Composite/Prediction.yml

@@ -5,24 +5,19 @@ Predictor:
       models:
         '0':
           ref: VBoussot/impact-torchscript-models:MIND/R1D2_3D.pt
-          voxel_size:
-          - 3.0
-          - 3.0
-          - 3.0
           layers_mask: '1'
-          layers_weight: 1.0
+          layers_weight:
+          - 1.0
           pca: 0
-          distance: L1
-      overlap: 2
+          distance: L2
       mixed_precision: false
       grid_spacing: 6
       displacement_half_width: 4
       iterations: 80
-      learning_rate: 1.0
+      learning_rate: 2.0
       regularization_weight: 1.25
       grid_shrink: 2
       control_grid_smoothing: 3
-      subset_features: []
       linear: true
       linear_iterations: 200
       seed: 42
@@ -80,10 +75,15 @@ Predictor:
             prob: 1
         nb: 2
     Patch:
-      patch_size: [0, 0, 0]
+      patch_size:
+      - 0
+      - 0
+      - 0
       overlap: 20%
       pad_value: None
       extend_slice: 0
+      mode: resample
+      max_voxels: None
     subset: None
     dataset_filenames:
     - ./Dataset/:mha

ConvexAdam_Composite/Prediction_tile.yml

@@ -0,0 +1,115 @@
+Predictor:
+  Model:
+    classpath: impact_reg_konfai.models.convexadam:RegistrationNet
+    RegistrationNet:
+      models:
+        '0':
+          ref: VBoussot/impact-torchscript-models:MIND/R1D2_3D.pt
+          layers_mask: '1'
+          layers_weight:
+          - 1.0
+          pca: 0
+          distance: L2
+      mixed_precision: false
+      grid_spacing: 6
+      displacement_half_width: 4
+      iterations: 80
+      learning_rate: 2.0
+      regularization_weight: 1.25
+      grid_shrink: 2
+      control_grid_smoothing: 3
+      linear: false
+      linear_iterations: 200
+      seed: 42
+      outputs_criterions: None
+      stages:
+      - fine
+  Dataset:
+    groups_src:
+      Volume_0:
+        groups_dest:
+          Fixed:
+            transforms:
+              TensorCast:
+                dtype: float32
+                inverse: false
+            patch_transforms: None
+            is_input: true
+      Volume_1:
+        groups_dest:
+          Moving:
+            transforms:
+              TensorCast:
+                dtype: float32
+                inverse: false
+            patch_transforms: None
+            is_input: true
+      Volume_2:
+        groups_dest:
+          FixedMask:
+            transforms:
+              TensorCast:
+                dtype: float32
+                inverse: false
+            patch_transforms: None
+            is_input: true
+      Volume_3:
+        groups_dest:
+          MovingMask:
+            transforms:
+              TensorCast:
+                dtype: float32
+                inverse: false
+            patch_transforms: None
+            is_input: true
+    augmentations:
+      DataAugmentation_0:
+        data_augmentations:
+          Flip:
+            f_prob:
+            - 0
+            - 0.5
+            - 0.5
+            vector_field: true
+            prob: 1
+        nb: 2
+    Patch:
+      patch_size:
+      - 0
+      - 0
+      - 0
+      overlap: 20%
+      pad_value: None
+      extend_slice: 0
+      mode: tile
+      max_voxels: None
+    subset: None
+    dataset_filenames:
+    - ./Dataset/:mha
+    batch_size: 1
+    num_workers: None
+    pin_memory: false
+    prefetch_factor: None
+    persistent_workers: None
+  outputs_dataset:
+    DisplacementField:
+      OutputDataset:
+        name_class: OutputDataset
+        before_reduction_transforms: None
+        after_reduction_transforms: None
+        final_transforms:
+          TensorCast:
+            dtype: float32
+            inverse: false
+        dataset_filename: Transform:itktransform
+        group: Transform
+        same_as_group: Volume_0:Fixed
+        patch_combine: Cosinus
+        reduction: Mean
+        Mean: {}
+  train_name: ImpactReg-ConvexAdam-Composite
+  manual_seed: 42
+  gpu_checkpoints: None
+  combine: Mean
+  autocast: false
+  data_log: None

ConvexAdam_Composite/app.json

@@ -1,7 +1,7 @@
 {
     "display_name": "ConvexAdam (MIND)",
     "short_description": "Coarse + fine ConvexAdam registration in one app (IMPACT/MIND features).",
-    "description": "The full ConvexAdam pipeline chained in one app: optional moments+affine linear pre-align, then a ConvexAdam coarse coupled-convex initialization, then an Adam instance-optimisation refinement, all driven by the IMPACT metric on MIND features. Produces the moved image and the displacement field on the fixed grid.",
+    "description": "The full ConvexAdam pipeline chained in one app: optional moments+affine linear pre-align, then a ConvexAdam coarse coupled-convex initialization, then an Adam instance-optimisation refinement, all driven by the IMPACT metric on MIND features. Produces the displacement field on the fixed grid, from which impact-reg-konfai derives the moved image.",
     "task": "registration",
     "tta": 0,
     "mc_dropout": 0,
@@ -85,5 +85,20 @@
                 }
             }
         }
-    }
+    },
+    "vram_bytes_per_voxel": 350,
+    "tiling": {
+        "global": "Prediction.yml",
+        "tile": "Prediction_tile.yml",
+        "tile_vram_bytes_per_voxel": 350,
+        "tile_ram_bytes_per_voxel": 800
+    },
+    "ram_bytes_per_voxel": 800,
+    "model_files": [
+        {
+            "repo_id": "VBoussot/impact-torchscript-models",
+            "revision": "47ffad660e67cebbac8d74aecf0fa181c5dac042",
+            "filename": "MIND/R1D2_3D.pt"
+        }
+    ]
 }

ConvexAdam_Composite/requirements.txt

@@ -1,2 +1,2 @@
-itk-impact>=0.1.1
+itk-impact==0.1.6
 impact_reg_konfai>=1.7.0

ConvexAdam_IMPACT_CBCT/Evaluation_with_fid.yml

@@ -0,0 +1,22 @@
+Evaluator:
+  metrics:
+    FixedFid:
+      targets_criterions:
+        MovingFid:
+          criterions_loader:
+            TRE: {}
+  Dataset:
+    groups_src:
+      Volume_0:
+        groups_dest:
+          FixedFid:
+            transforms: None
+      Reference_0:
+        groups_dest:
+          MovingFid:
+            transforms: None
+    subset: None
+    dataset_filenames:
+    - ./Dataset:mha
+    validation: None
+  train_name: ImpactReg

ConvexAdam_IMPACT_CBCT/Evaluation_with_images.yml

@@ -0,0 +1,35 @@
+Evaluator:
+  metrics:
+    FixedImage:
+      targets_criterions:
+        MovingImage;Mask:
+          criterions_loader:
+            MAESaveMap:
+              reduction: mean
+              dataset: ./Evaluations/ImpactReg/Output:mha
+              group: MAE_map
+  Dataset:
+    groups_src:
+      Volume_0:
+        groups_dest:
+          FixedImage:
+            transforms: 
+              TensorCast:
+                dtype: float32
+      Reference_0:
+        groups_dest:
+          MovingImage:
+            transforms: 
+              TensorCast:
+                dtype: float32
+      Mask_0:
+        groups_dest:
+          Mask:
+            transforms:
+              TensorCast:
+                dtype: uint8
+    subset: None
+    dataset_filenames:
+    - ./Dataset:mha
+    validation: None
+  train_name: ImpactReg

ConvexAdam_IMPACT_CBCT/Evaluation_with_seg.yml

@@ -0,0 +1,29 @@
+Evaluator:
+  metrics:
+    FixedSeg:
+      targets_criterions:
+        MovingSeg:
+          criterions_loader:
+            DiceSaveMap:
+              labels: None
+              dataset: ./Evaluations/ImpactReg/Output:mha
+              group: Seg_MAE_map
+  Dataset:
+    groups_src:
+      Volume_0:
+        groups_dest:
+          FixedSeg:
+            transforms: 
+              TensorCast:
+                dtype: uint8
+      Reference_0:
+        groups_dest:
+          MovingSeg:
+            transforms: 
+              TensorCast:
+                dtype: uint8
+    subset: None
+    dataset_filenames:
+    - ./Dataset:mha
+    validation: None
+  train_name: ImpactReg

ConvexAdam_IMPACT_CBCT/Prediction.yml

@@ -0,0 +1,123 @@
+Predictor:
+  Model:
+    classpath: impact_reg_konfai.models.convexadam:RegistrationNet
+    RegistrationNet:
+      models:
+        '0':
+          ref: VBoussot/impact-torchscript-models:MIND/R1D2_3D.pt
+          layers_mask: '1'
+          layers_weight:
+          - 1.0
+          pca: 0
+          distance: L2
+        '1':
+          ref: VBoussot/impact-torchscript-models:TS/M730.pt
+          layers_mask: '01'
+          layers_weight:
+          - 1.0
+          pca: 0
+          distance: L2
+      mixed_precision: false
+      grid_spacing: 6
+      displacement_half_width: 4
+      iterations: 80
+      learning_rate: 2.0
+      regularization_weight: 5.0
+      grid_shrink: 2
+      control_grid_smoothing: 3
+      linear: true
+      linear_iterations: 200
+      seed: 42
+      outputs_criterions: None
+      stages:
+      - coarse
+      - fine
+  Dataset:
+    groups_src:
+      Volume_0:
+        groups_dest:
+          Fixed:
+            transforms:
+              TensorCast:
+                dtype: float32
+                inverse: false
+            patch_transforms: None
+            is_input: true
+      Volume_1:
+        groups_dest:
+          Moving:
+            transforms:
+              TensorCast:
+                dtype: float32
+                inverse: false
+            patch_transforms: None
+            is_input: true
+      Volume_2:
+        groups_dest:
+          FixedMask:
+            transforms:
+              TensorCast:
+                dtype: float32
+                inverse: false
+            patch_transforms: None
+            is_input: true
+      Volume_3:
+        groups_dest:
+          MovingMask:
+            transforms:
+              TensorCast:
+                dtype: float32
+                inverse: false
+            patch_transforms: None
+            is_input: true
+    augmentations:
+      DataAugmentation_0:
+        data_augmentations:
+          Flip:
+            f_prob:
+            - 0
+            - 0.5
+            - 0.5
+            vector_field: true
+            prob: 1
+        nb: 2
+    Patch:
+      patch_size:
+      - 0
+      - 0
+      - 0
+      overlap: 20%
+      pad_value: None
+      extend_slice: 0
+      mode: resample
+      max_voxels: None
+    subset: None
+    dataset_filenames:
+    - ./Dataset/:mha
+    batch_size: 1
+    num_workers: None
+    pin_memory: false
+    prefetch_factor: None
+    persistent_workers: None
+  outputs_dataset:
+    DisplacementField:
+      OutputDataset:
+        name_class: OutputDataset
+        before_reduction_transforms: None
+        after_reduction_transforms: None
+        final_transforms:
+          TensorCast:
+            dtype: float32
+            inverse: false
+        dataset_filename: Transform:itktransform
+        group: Transform
+        same_as_group: Volume_0:Fixed
+        patch_combine: Cosinus
+        reduction: Mean
+        Mean: {}
+  train_name: ImpactReg-ConvexAdam-IMPACT-CBCT
+  manual_seed: 42
+  gpu_checkpoints: None
+  combine: Mean
+  autocast: false
+  data_log: None

ConvexAdam_IMPACT_CBCT/Prediction_tile.yml

@@ -0,0 +1,122 @@
+Predictor:
+  Model:
+    classpath: impact_reg_konfai.models.convexadam:RegistrationNet
+    RegistrationNet:
+      models:
+        '0':
+          ref: VBoussot/impact-torchscript-models:MIND/R1D2_3D.pt
+          layers_mask: '1'
+          layers_weight:
+          - 1.0
+          pca: 0
+          distance: L2
+        '1':
+          ref: VBoussot/impact-torchscript-models:TS/M730.pt
+          layers_mask: '01'
+          layers_weight:
+          - 1.0
+          pca: 0
+          distance: L2
+      mixed_precision: false
+      grid_spacing: 6
+      displacement_half_width: 4
+      iterations: 80
+      learning_rate: 2.0
+      regularization_weight: 5.0
+      grid_shrink: 2
+      control_grid_smoothing: 3
+      linear: false
+      linear_iterations: 200
+      seed: 42
+      outputs_criterions: None
+      stages:
+      - fine
+  Dataset:
+    groups_src:
+      Volume_0:
+        groups_dest:
+          Fixed:
+            transforms:
+              TensorCast:
+                dtype: float32
+                inverse: false
+            patch_transforms: None
+            is_input: true
+      Volume_1:
+        groups_dest:
+          Moving:
+            transforms:
+              TensorCast:
+                dtype: float32
+                inverse: false
+            patch_transforms: None
+            is_input: true
+      Volume_2:
+        groups_dest:
+          FixedMask:
+            transforms:
+              TensorCast:
+                dtype: float32
+                inverse: false
+            patch_transforms: None
+            is_input: true
+      Volume_3:
+        groups_dest:
+          MovingMask:
+            transforms:
+              TensorCast:
+                dtype: float32
+                inverse: false
+            patch_transforms: None
+            is_input: true
+    augmentations:
+      DataAugmentation_0:
+        data_augmentations:
+          Flip:
+            f_prob:
+            - 0
+            - 0.5
+            - 0.5
+            vector_field: true
+            prob: 1
+        nb: 2
+    Patch:
+      patch_size:
+      - 0
+      - 0
+      - 0
+      overlap: 20%
+      pad_value: None
+      extend_slice: 0
+      mode: tile
+      max_voxels: None
+    subset: None
+    dataset_filenames:
+    - ./Dataset/:mha
+    batch_size: 1
+    num_workers: None
+    pin_memory: false
+    prefetch_factor: None
+    persistent_workers: None
+  outputs_dataset:
+    DisplacementField:
+      OutputDataset:
+        name_class: OutputDataset
+        before_reduction_transforms: None
+        after_reduction_transforms: None
+        final_transforms:
+          TensorCast:
+            dtype: float32
+            inverse: false
+        dataset_filename: Transform:itktransform
+        group: Transform
+        same_as_group: Volume_0:Fixed
+        patch_combine: Cosinus
+        reduction: Mean
+        Mean: {}
+  train_name: ImpactReg-ConvexAdam-IMPACT-CBCT
+  manual_seed: 42
+  gpu_checkpoints: None
+  combine: Mean
+  autocast: false
+  data_log: None

ConvexAdam_IMPACT_CBCT/Uncertainty.yml

@@ -0,0 +1,24 @@
+Evaluator:
+  metrics:
+    Uncertainty:
+      targets_criterions:
+        None:
+          criterions_loader:
+            Mean:
+              name: Uncertainty
+  Dataset:
+    groups_src:
+      Volume_0:
+        groups_dest:
+          Uncertainty:
+            transforms:
+              Norm: {}
+              StandardDeviation: {}
+              Save:
+                dataset: ./Uncertainties/ImpactReg/Output:mha
+                group: None
+    subset: None
+    dataset_filenames:
+    - ./Dataset:mha
+    validation: None
+  train_name: ImpactReg

ConvexAdam_IMPACT_CBCT/app.json

@@ -0,0 +1,109 @@
+{
+    "display_name": "ConvexAdam, MIND + TotalSegmentator MR early layer",
+    "short_description": "ConvexAdam_Composite (MIND) with the second layer of TotalSegmentator MR (TS/M730) added, for CT/CBCT.",
+    "description": "ConvexAdam_Composite (MIND) with the second layer of TotalSegmentator MR (TS/M730) added, for CT/CBCT. Everything else is ConvexAdam_Composite's (the affine pre-alignment on mutual information, the coupled-convex coarse search, then the Adam refinement, on both feature models) except the refinement's regularisation, raised to 5: with the refinement's IMPACT loss normalised (every feature layer starts at 1), thorax CBCT folded 2.0 % of the body at 2.5 and 0.3 % at 5 (Dice 0.496 and 0.498), OASIS 0.9 % and 0.1 %, AbdomenCTCT 0.75 % and 0.01 %.",
+    "task": "registration",
+    "tta": 0,
+    "mc_dropout": 0,
+    "models": [],
+    "inputs": {
+        "Fixed": {
+            "display_name": "Fixed image",
+            "volume_type": "VOLUME",
+            "required": true
+        },
+        "Moving": {
+            "display_name": "Moving image",
+            "volume_type": "VOLUME",
+            "required": true
+        },
+        "FixedMask": {
+            "display_name": "Fixed mask (optional)",
+            "volume_type": "SEGMENTATION",
+            "required": false,
+            "default": "ones"
+        },
+        "MovingMask": {
+            "display_name": "Moving mask (optional)",
+            "volume_type": "SEGMENTATION",
+            "required": false,
+            "default": "ones"
+        }
+    },
+    "outputs": {
+        "DisplacementField": {
+            "display_name": "Displacement field",
+            "volume_type": "VOLUME",
+            "required": true
+        }
+    },
+    "inputs_evaluations": {
+        "Image": {
+            "Evaluation_with_images.yml": {
+                "FixedImage": {
+                    "display_name": "Fixed image",
+                    "volume_type": "VOLUME",
+                    "required": true
+                },
+                "MovingImage": {
+                    "display_name": "Moving image",
+                    "volume_type": "VOLUME",
+                    "required": true
+                },
+                "Mask": {
+                    "display_name": "Evaluation mask",
+                    "volume_type": "SEGMENTATION",
+                    "required": false
+                }
+            }
+        },
+        "Segmentation": {
+            "Evaluation_with_seg.yml": {
+                "FixedSeg": {
+                    "display_name": "Fixed segmentation",
+                    "volume_type": "SEGMENTATION",
+                    "required": true
+                },
+                "MovingSeg": {
+                    "display_name": "Moving segmentation",
+                    "volume_type": "SEGMENTATION",
+                    "required": true
+                }
+            }
+        },
+        "Landmarks": {
+            "Evaluation_with_fid.yml": {
+                "FixedFid": {
+                    "display_name": "Fixed landmarks",
+                    "volume_type": "FIDUCIALS",
+                    "required": true
+                },
+                "MovingFid": {
+                    "display_name": "Moving landmarks",
+                    "volume_type": "FIDUCIALS",
+                    "required": true
+                }
+            }
+        }
+    },
+    "vram_bytes_per_voxel": 650,
+    "tiling": {
+        "global": "Prediction.yml",
+        "tile": "Prediction_tile.yml",
+        "tile_vram_bytes_per_voxel": 650,
+        "tile_ram_bytes_per_voxel": 1200
+    },
+    "ram_bytes_per_voxel": 1200,
+    "model_files": [
+        {
+            "repo_id": "VBoussot/impact-torchscript-models",
+            "revision": "47ffad660e67cebbac8d74aecf0fa181c5dac042",
+            "filename": "MIND/R1D2_3D.pt"
+        },
+        {
+            "repo_id": "VBoussot/impact-torchscript-models",
+            "revision": "47ffad660e67cebbac8d74aecf0fa181c5dac042",
+            "filename": "TS/M730.pt"
+        }
+    ]
+}

ConvexAdam_IMPACT_CBCT/requirements.txt

@@ -0,0 +1,2 @@
+itk-impact==0.1.6
+impact_reg_konfai>=1.7.0

ConvexAdam_IMPACT_MRCT/Evaluation_with_fid.yml

@@ -0,0 +1,22 @@
+Evaluator:
+  metrics:
+    FixedFid:
+      targets_criterions:
+        MovingFid:
+          criterions_loader:
+            TRE: {}
+  Dataset:
+    groups_src:
+      Volume_0:
+        groups_dest:
+          FixedFid:
+            transforms: None
+      Reference_0:
+        groups_dest:
+          MovingFid:
+            transforms: None
+    subset: None
+    dataset_filenames:
+    - ./Dataset:mha
+    validation: None
+  train_name: ImpactReg

ConvexAdam_IMPACT_MRCT/Evaluation_with_images.yml

@@ -0,0 +1,35 @@
+Evaluator:
+  metrics:
+    FixedImage:
+      targets_criterions:
+        MovingImage;Mask:
+          criterions_loader:
+            MAESaveMap:
+              reduction: mean
+              dataset: ./Evaluations/ImpactReg/Output:mha
+              group: MAE_map
+  Dataset:
+    groups_src:
+      Volume_0:
+        groups_dest:
+          FixedImage:
+            transforms: 
+              TensorCast:
+                dtype: float32
+      Reference_0:
+        groups_dest:
+          MovingImage:
+            transforms: 
+              TensorCast:
+                dtype: float32
+      Mask_0:
+        groups_dest:
+          Mask:
+            transforms:
+              TensorCast:
+                dtype: uint8
+    subset: None
+    dataset_filenames:
+    - ./Dataset:mha
+    validation: None
+  train_name: ImpactReg

ConvexAdam_IMPACT_MRCT/Evaluation_with_seg.yml

@@ -0,0 +1,29 @@
+Evaluator:
+  metrics:
+    FixedSeg:
+      targets_criterions:
+        MovingSeg:
+          criterions_loader:
+            DiceSaveMap:
+              labels: None
+              dataset: ./Evaluations/ImpactReg/Output:mha
+              group: Seg_MAE_map
+  Dataset:
+    groups_src:
+      Volume_0:
+        groups_dest:
+          FixedSeg:
+            transforms: 
+              TensorCast:
+                dtype: uint8
+      Reference_0:
+        groups_dest:
+          MovingSeg:
+            transforms: 
+              TensorCast:
+                dtype: uint8
+    subset: None
+    dataset_filenames:
+    - ./Dataset:mha
+    validation: None
+  train_name: ImpactReg

ConvexAdam_IMPACT_MRCT/Prediction.yml

@@ -0,0 +1,122 @@
+Predictor:
+  Model:
+    classpath: impact_reg_konfai.models.convexadam:RegistrationNet
+    RegistrationNet:
+      models:
+        '0':
+          ref: VBoussot/impact-torchscript-models:MIND/R1D2_3D.pt
+          layers_mask: '1'
+          layers_weight:
+          - 1.0
+          pca: 0
+          distance: L2
+        '1':
+          ref: VBoussot/impact-torchscript-models:TS/M730.pt
+          layers_mask: '00000001'
+          layers_weight:
+          - 1.0
+          pca: 0
+          distance: L2
+      mixed_precision: false
+      grid_spacing: 6
+      displacement_half_width: 4
+      iterations: 80
+      learning_rate: 2.0
+      regularization_weight: 2.5
+      grid_shrink: 2
+      control_grid_smoothing: 3
+      linear: true
+      linear_iterations: 200
+      seed: 42
+      outputs_criterions: None
+      stages:
+      - coarse
+  Dataset:
+    groups_src:
+      Volume_0:
+        groups_dest:
+          Fixed:
+            transforms:
+              TensorCast:
+                dtype: float32
+                inverse: false
+            patch_transforms: None
+            is_input: true
+      Volume_1:
+        groups_dest:
+          Moving:
+            transforms:
+              TensorCast:
+                dtype: float32
+                inverse: false
+            patch_transforms: None
+            is_input: true
+      Volume_2:
+        groups_dest:
+          FixedMask:
+            transforms:
+              TensorCast:
+                dtype: float32
+                inverse: false
+            patch_transforms: None
+            is_input: true
+      Volume_3:
+        groups_dest:
+          MovingMask:
+            transforms:
+              TensorCast:
+                dtype: float32
+                inverse: false
+            patch_transforms: None
+            is_input: true
+    augmentations:
+      DataAugmentation_0:
+        data_augmentations:
+          Flip:
+            f_prob:
+            - 0
+            - 0.5
+            - 0.5
+            vector_field: true
+            prob: 1
+        nb: 2
+    Patch:
+      patch_size:
+      - 0
+      - 0
+      - 0
+      overlap: 20%
+      pad_value: None
+      extend_slice: 0
+      mode: resample
+      max_voxels: None
+    subset: None
+    dataset_filenames:
+    - ./Dataset/:mha
+    batch_size: 1
+    num_workers: None
+    pin_memory: false
+    prefetch_factor: None
+    persistent_workers: None
+  outputs_dataset:
+    DisplacementField:
+      OutputDataset:
+        name_class: OutputDataset
+        before_reduction_transforms: None
+        after_reduction_transforms: None
+        final_transforms:
+          TensorCast:
+            dtype: float32
+            inverse: false
+        dataset_filename: Transform:itktransform
+        group: Transform
+        same_as_group: Volume_0:Fixed
+        patch_combine: Cosinus
+        reduction: Mean
+        Mean: {}
+  train_name: ImpactReg-ConvexAdam-IMPACT-MRCT
+  manual_seed: 42
+  gpu_checkpoints: None
+  combine: Mean
+  autocast: false
+  data_log: None

ConvexAdam_IMPACT_MRCT/Uncertainty.yml

@@ -0,0 +1,24 @@
+Evaluator:
+  metrics:
+    Uncertainty:
+      targets_criterions:
+        None:
+          criterions_loader:
+            Mean:
+              name: Uncertainty
+  Dataset:
+    groups_src:
+      Volume_0:
+        groups_dest:
+          Uncertainty:
+            transforms:
+              Norm: {}
+              StandardDeviation: {}
+              Save:
+                dataset: ./Uncertainties/ImpactReg/Output:mha
+                group: None
+    subset: None
+    dataset_filenames:
+    - ./Dataset:mha
+    validation: None
+  train_name: ImpactReg

ConvexAdam_IMPACT_MRCT/app.json

@@ -0,0 +1,106 @@
+{
+    "display_name": "ConvexAdam, MIND + TotalSegmentator MR segmentation",
+    "short_description": "ConvexAdam's coarse search on MIND and the segmentation head of TotalSegmentator MR (TS/M730), for MR/CT.",
+    "description": "ConvexAdam's coupled-convex coarse search on MIND and the segmentation head of TotalSegmentator MR (TS/M730), for MR/CT: the one-hot map of its 30 structures, compared by squared differences like MIND, after the affine pre-alignment on mutual information. No Adam refinement: on MR/CT pairs the refinement folded 1 to 2 % of the body and cost the head-and-neck pair about 0.2 of Dice, where the coarse field alone reached a Dice of 0.665, 0.599 and 0.686 on the Learn2Reg abdomen, SynthRAD abdomen and SynthRAD head-and-neck MR/CT pairs, with no fold.",
+    "task": "registration",
+    "tta": 0,
+    "mc_dropout": 0,
+    "models": [],
+    "inputs": {
+        "Fixed": {
+            "display_name": "Fixed image",
+            "volume_type": "VOLUME",
+            "required": true
+        },
+        "Moving": {
+            "display_name": "Moving image",
+            "volume_type": "VOLUME",
+            "required": true
+        },
+        "FixedMask": {
+            "display_name": "Fixed mask (optional)",
+            "volume_type": "SEGMENTATION",
+            "required": false,
+            "default": "ones"
+        },
+        "MovingMask": {
+            "display_name": "Moving mask (optional)",
+            "volume_type": "SEGMENTATION",
+            "required": false,
+            "default": "ones"
+        }
+    },
+    "outputs": {
+        "DisplacementField": {
+            "display_name": "Displacement field",
+            "volume_type": "VOLUME",
+            "required": true
+        }
+    },
+    "inputs_evaluations": {
+        "Image": {
+            "Evaluation_with_images.yml": {
+                "FixedImage": {
+                    "display_name": "Fixed image",
+                    "volume_type": "VOLUME",
+                    "required": true
+                },
+                "MovingImage": {
+                    "display_name": "Moving image",
+                    "volume_type": "VOLUME",
+                    "required": true
+                },
+                "Mask": {
+                    "display_name": "Evaluation mask",
+                    "volume_type": "SEGMENTATION",
+                    "required": false
+                }
+            }
+        },
+        "Segmentation": {
+            "Evaluation_with_seg.yml": {
+                "FixedSeg": {
+                    "display_name": "Fixed segmentation",
+                    "volume_type": "SEGMENTATION",
+                    "required": true
+                },
+                "MovingSeg": {
+                    "display_name": "Moving segmentation",
+                    "volume_type": "SEGMENTATION",
+                    "required": true
+                }
+            }
+        },
+        "Landmarks": {
+            "Evaluation_with_fid.yml": {
+                "FixedFid": {
+                    "display_name": "Fixed landmarks",
+                    "volume_type": "FIDUCIALS",
+                    "required": true
+                },
+                "MovingFid": {
+                    "display_name": "Moving landmarks",
+                    "volume_type": "FIDUCIALS",
+                    "required": true
+                }
+            }
+        }
+    },
+    "vram_bytes_per_voxel": 1150,
+    "tiling": {
+        "global": "Prediction.yml"
+    },
+    "ram_bytes_per_voxel": 2050,
+    "model_files": [
+        {
+            "repo_id": "VBoussot/impact-torchscript-models",
+            "revision": "47ffad660e67cebbac8d74aecf0fa181c5dac042",
+            "filename": "MIND/R1D2_3D.pt"
+        },
+        {
+            "repo_id": "VBoussot/impact-torchscript-models",
+            "revision": "47ffad660e67cebbac8d74aecf0fa181c5dac042",
+            "filename": "TS/M730.pt"
+        }
+    ]
+}

ConvexAdam_IMPACT_MRCT/requirements.txt

@@ -0,0 +1,2 @@
+itk-impact==0.1.6
+impact_reg_konfai>=1.7.0

Elastix_IMPACT_Jacobian/ParameterMap_Jacobian.txt

@@ -5,6 +5,7 @@
 (FinalGridSpacingInPhysicalUnits 10)
 (FixedImagePyramid "FixedGenericImagePyramid")
 (MovingImagePyramid "MovingGenericImagePyramid")
+(ComputePyramidImagesPerResolution "true")
 (FixedImagePyramidRescaleSchedule 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1)
 (MovingImagePyramidRescaleSchedule 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1)
 // (GridSpacingSchedule 10.000000 5.000000 2.000000 1.000000)

Elastix_IMPACT_Jacobian/Parameters_Rigid.txt

@@ -0,0 +1,147 @@
+// Example parameter file for rotation registration
+// C-style comments: //
+
+// The internal pixel type, used for internal computations
+// Leave to float in general. 
+// NB: this is not the type of the input images! The pixel 
+// type of the input images is automatically read from the 
+// images themselves.
+// This setting can be changed to "short" to save some memory
+// in case of very large 3D images.
+(FixedInternalImagePixelType "float")
+(MovingInternalImagePixelType "float")
+
+// **************** Main Components **************************
+
+// The following components should usually be left as they are:
+(Registration "MultiResolutionRegistration")
+(Interpolator "BSplineInterpolator")
+(ResampleInterpolator "FinalBSplineInterpolator")
+(Resampler "DefaultResampler")
+
+// These may be changed to Fixed/MovingSmoothingImagePyramid.
+// See the manual.
+(FixedImagePyramid "FixedRecursiveImagePyramid")
+(MovingImagePyramid "MovingRecursiveImagePyramid")
+
+// The following components are most important:
+// The optimizer AdaptiveStochasticGradientDescent (ASGD) works
+// quite ok in general. The Transform and Metric are important
+// and need to be chosen careful for each application. See manual.
+(Optimizer "AdaptiveStochasticGradientDescent")
+(Transform "EulerTransform")
+(Metric "AdvancedMattesMutualInformation")
+
+// ***************** Transformation **************************
+
+// Scales the rotations compared to the translations, to make
+// sure they are in the same range. In general, it's best to  
+// use automatic scales estimation:
+(AutomaticScalesEstimation "true")
+
+// Automatically guess an initial translation by aligning the
+// geometric centers of the fixed and moving.
+(AutomaticTransformInitialization "true")
+
+// Whether transforms are combined by composition or by addition.
+// In generally, Compose is the best option in most cases.
+// It does not influence the results very much.
+(HowToCombineTransforms "Compose")
+
+//Save composite ITK transform
+(ITKTransformOutputFileNameExtension "itk.txt")
+(WriteITKCompositeTransform "true")
+
+// ******************* Similarity measure *********************
+
+// Number of grey level bins in each resolution level,
+// for the mutual information. 16 or 32 usually works fine.
+// You could also employ a hierarchical strategy:
+//(NumberOfHistogramBins 16 32 64)
+(NumberOfHistogramBins 32)
+
+// If you use a mask, this option is important. 
+// If the mask serves as region of interest, set it to false.
+// If the mask indicates which pixels are valid, then set it to true.
+// If you do not use a mask, the option doesn't matter.
+(ErodeMask "false")
+
+// ******************** Multiresolution **********************
+
+// The number of resolutions. 1 Is only enough if the expected
+// deformations are small. 3 or 4 mostly works fine. For large
+// images and large deformations, 5 or 6 may even be useful.
+(NumberOfResolutions 4)
+
+// The downsampling/blurring factors for the image pyramids.
+// By default, the images are downsampled by a factor of 2
+// compared to the next resolution.
+// So, in 2D, with 4 resolutions, the following schedule is used:
+//(ImagePyramidSchedule 8 8  4 4  2 2  1 1 )
+// And in 3D:
+//(ImagePyramidSchedule 8 8 8  4 4 4  2 2 2  1 1 1 )
+// You can specify any schedule, for example:
+//(ImagePyramidSchedule 4 4  4 3  2 1  1 1 )
+// Make sure that the number of elements equals the number
+// of resolutions times the image dimension.
+
+// ******************* Optimizer ****************************
+
+// Maximum number of iterations in each resolution level:
+// 200-500 works usually fine for rigid registration.
+// For more robustness, you may increase this to 1000-2000.
+(MaximumNumberOfIterations 250)
+
+// The step size of the optimizer, in mm. By default the voxel size is used.
+// which usually works well. In case of unusual high-resolution images
+// (eg histology) it is necessary to increase this value a bit, to the size
+// of the "smallest visible structure" in the image:
+//(MaximumStepLength 1.0)
+
+// **************** Image sampling **********************
+
+// Number of spatial samples used to compute the mutual
+// information (and its derivative) in each iteration.
+// With an AdaptiveStochasticGradientDescent optimizer,
+// in combination with the two options below, around 2000
+// samples may already suffice.
+(NumberOfSpatialSamples 2048)
+
+// Refresh these spatial samples in every iteration, and select
+// them randomly. See the manual for information on other sampling
+// strategies.
+(NewSamplesEveryIteration "true")
+(ImageSampler "Random")
+
+// ************* Interpolation and Resampling ****************
+
+// Order of B-Spline interpolation used during registration/optimisation.
+// It may improve accuracy if you set this to 3. Never use 0.
+// An order of 1 gives linear interpolation. This is in most 
+// applications a good choice.
+(BSplineInterpolationOrder 1)
+
+// Order of B-Spline interpolation used for applying the final
+// deformation.
+// 3 gives good accuracy; recommended in most cases.
+// 1 gives worse accuracy (linear interpolation)
+// 0 gives worst accuracy, but is appropriate for binary images
+// (masks, segmentations); equivalent to nearest neighbor interpolation.
+(FinalBSplineInterpolationOrder 3)
+
+//Default pixel value for pixels that come from outside the picture:
+(DefaultPixelValue 0)
+
+// Choose whether to generate the deformed moving image.
+// You can save some time by setting this to false, if you are
+// only interested in the final (nonrigidly) deformed moving image
+// for example.
+(WriteResultImage "false")
+
+// The pixel type and format of the resulting deformed moving image
+(ResultImagePixelType "short")
+(ResultImageFormat "mha")
+(WriteTransformParametersEachIteration "false")
+(WriteTransformParametersEachResolution "false")
+(WriteIterationInfo "false")
+

Elastix_IMPACT_Jacobian/Prediction.yml

@@ -4,23 +4,23 @@ Predictor:
     RegistrationNet:
       engine: elastix
       parameter_maps:
+      - Parameters_Rigid.txt
       - ParameterMap_Jacobian.txt
       outputs_criterions: None
       max_iterations: 0
       final_grid_spacing: 10.0
-      subset_features: 0
       spatial_samples: 2000
       parameter_overrides: []
-      resolutions:
+      levels:
         '0':
           max_iterations: 300
           models:
             '0':
               ref: VBoussot/impact-torchscript-models:TS/M730.pt
               voxel_size:
-              - 6.0
-              - 6.0
-              - 6.0
+              - 3.0
+              - 3.0
+              - 3.0
               layers_mask: '01'
               layers_weight:
               - 1.0
@@ -88,6 +88,7 @@ Predictor:
               pca: 0
               distance: L1
       mode: Jacobian
+      mixed_precision: true
   Dataset:
     groups_src:
       Volume_0:
@@ -145,6 +146,8 @@ Predictor:
       overlap: 20%
       pad_value: None
       extend_slice: 0
+      mode: resample
+      max_voxels: None
     subset: None
     dataset_filenames:
     - ./Dataset/:mha

Elastix_IMPACT_Jacobian/app.json

@@ -1,7 +1,7 @@
 {
     "display_name": "elastix + IMPACT (Jacobian), TotalSegmentator M730",
-    "short_description": "elastix B-spline driven by IMPACT on TotalSegmentator M730, early layers, Jacobian mode: the loss is differentiated through the network on a patch sized to the layers' field of view. The pairing that suits CT and CBCT, where texture carries the alignment.",
-    "description": "elastix B-spline driven by IMPACT on TotalSegmentator M730, early layers, Jacobian mode: the loss is differentiated through the network on a patch sized to the layers' field of view. The pairing that suits CT and CBCT, where texture carries the alignment.",
+    "short_description": "A rigid alignment on mutual information, then an elastix B-spline driven by IMPACT on TotalSegmentator M730, early layers, Jacobian mode: the loss is differentiated through the network on a patch sized to the layers' field of view. The pairing that suits CT and CBCT, where texture carries the alignment.",
+    "description": "A rigid alignment on mutual information, then an elastix B-spline driven by IMPACT on TotalSegmentator M730, early layers, Jacobian mode: the loss is differentiated through the network on a patch sized to the layers' field of view. The pairing that suits CT and CBCT, where texture carries the alignment.",
     "task": "registration",
     "tta": 0,
     "mc_dropout": 0,
@@ -85,5 +85,17 @@
                 }
             }
         }
-    }
-}
+    },
+    "vram_bytes_per_voxel": 350,
+    "tiling": {
+        "global": "Prediction.yml"
+    },
+    "ram_bytes_per_voxel": 1150,
+    "model_files": [
+        {
+            "repo_id": "VBoussot/impact-torchscript-models",
+            "revision": "47ffad660e67cebbac8d74aecf0fa181c5dac042",
+            "filename": "TS/M730.pt"
+        }
+    ]
+}

Elastix_IMPACT_Static/ParameterMap_Static.txt

@@ -5,6 +5,7 @@
 (FinalGridSpacingInPhysicalUnits 14)
 (FixedImagePyramid "FixedGenericImagePyramid")
 (MovingImagePyramid "MovingGenericImagePyramid")
+(ComputePyramidImagesPerResolution "true")
 (FixedImagePyramidRescaleSchedule 1 1 1 1 1 1 1 1 1 1 1 1)
 (MovingImagePyramidRescaleSchedule 1 1 1 1 1 1 1 1 1 1 1 1)
 // (GridSpacingSchedule 10.000000 5.000000 2.000000 1.000000)

Elastix_IMPACT_Static/Parameters_Rigid.txt

@@ -0,0 +1,147 @@
+// Example parameter file for rotation registration
+// C-style comments: //
+
+// The internal pixel type, used for internal computations
+// Leave to float in general. 
+// NB: this is not the type of the input images! The pixel 
+// type of the input images is automatically read from the 
+// images themselves.
+// This setting can be changed to "short" to save some memory
+// in case of very large 3D images.
+(FixedInternalImagePixelType "float")
+(MovingInternalImagePixelType "float")
+
+// **************** Main Components **************************
+
+// The following components should usually be left as they are:
+(Registration "MultiResolutionRegistration")
+(Interpolator "BSplineInterpolator")
+(ResampleInterpolator "FinalBSplineInterpolator")
+(Resampler "DefaultResampler")
+
+// These may be changed to Fixed/MovingSmoothingImagePyramid.
+// See the manual.
+(FixedImagePyramid "FixedRecursiveImagePyramid")
+(MovingImagePyramid "MovingRecursiveImagePyramid")
+
+// The following components are most important:
+// The optimizer AdaptiveStochasticGradientDescent (ASGD) works
+// quite ok in general. The Transform and Metric are important
+// and need to be chosen careful for each application. See manual.
+(Optimizer "AdaptiveStochasticGradientDescent")
+(Transform "EulerTransform")
+(Metric "AdvancedMattesMutualInformation")
+
+// ***************** Transformation **************************
+
+// Scales the rotations compared to the translations, to make
+// sure they are in the same range. In general, it's best to  
+// use automatic scales estimation:
+(AutomaticScalesEstimation "true")
+
+// Automatically guess an initial translation by aligning the
+// geometric centers of the fixed and moving.
+(AutomaticTransformInitialization "true")
+
+// Whether transforms are combined by composition or by addition.
+// In generally, Compose is the best option in most cases.
+// It does not influence the results very much.
+(HowToCombineTransforms "Compose")
+
+//Save composite ITK transform
+(ITKTransformOutputFileNameExtension "itk.txt")
+(WriteITKCompositeTransform "true")
+
+// ******************* Similarity measure *********************
+
+// Number of grey level bins in each resolution level,
+// for the mutual information. 16 or 32 usually works fine.
+// You could also employ a hierarchical strategy:
+//(NumberOfHistogramBins 16 32 64)
+(NumberOfHistogramBins 32)
+
+// If you use a mask, this option is important. 
+// If the mask serves as region of interest, set it to false.
+// If the mask indicates which pixels are valid, then set it to true.
+// If you do not use a mask, the option doesn't matter.
+(ErodeMask "false")
+
+// ******************** Multiresolution **********************
+
+// The number of resolutions. 1 Is only enough if the expected
+// deformations are small. 3 or 4 mostly works fine. For large
+// images and large deformations, 5 or 6 may even be useful.
+(NumberOfResolutions 4)
+
+// The downsampling/blurring factors for the image pyramids.
+// By default, the images are downsampled by a factor of 2
+// compared to the next resolution.
+// So, in 2D, with 4 resolutions, the following schedule is used:
+//(ImagePyramidSchedule 8 8  4 4  2 2  1 1 )
+// And in 3D:
+//(ImagePyramidSchedule 8 8 8  4 4 4  2 2 2  1 1 1 )
+// You can specify any schedule, for example:
+//(ImagePyramidSchedule 4 4  4 3  2 1  1 1 )
+// Make sure that the number of elements equals the number
+// of resolutions times the image dimension.
+
+// ******************* Optimizer ****************************
+
+// Maximum number of iterations in each resolution level:
+// 200-500 works usually fine for rigid registration.
+// For more robustness, you may increase this to 1000-2000.
+(MaximumNumberOfIterations 250)
+
+// The step size of the optimizer, in mm. By default the voxel size is used.
+// which usually works well. In case of unusual high-resolution images
+// (eg histology) it is necessary to increase this value a bit, to the size
+// of the "smallest visible structure" in the image:
+//(MaximumStepLength 1.0)
+
+// **************** Image sampling **********************
+
+// Number of spatial samples used to compute the mutual
+// information (and its derivative) in each iteration.
+// With an AdaptiveStochasticGradientDescent optimizer,
+// in combination with the two options below, around 2000
+// samples may already suffice.
+(NumberOfSpatialSamples 2048)
+
+// Refresh these spatial samples in every iteration, and select
+// them randomly. See the manual for information on other sampling
+// strategies.
+(NewSamplesEveryIteration "true")
+(ImageSampler "Random")
+
+// ************* Interpolation and Resampling ****************
+
+// Order of B-Spline interpolation used during registration/optimisation.
+// It may improve accuracy if you set this to 3. Never use 0.
+// An order of 1 gives linear interpolation. This is in most 
+// applications a good choice.
+(BSplineInterpolationOrder 1)
+
+// Order of B-Spline interpolation used for applying the final
+// deformation.
+// 3 gives good accuracy; recommended in most cases.
+// 1 gives worse accuracy (linear interpolation)
+// 0 gives worst accuracy, but is appropriate for binary images
+// (masks, segmentations); equivalent to nearest neighbor interpolation.
+(FinalBSplineInterpolationOrder 3)
+
+//Default pixel value for pixels that come from outside the picture:
+(DefaultPixelValue 0)
+
+// Choose whether to generate the deformed moving image.
+// You can save some time by setting this to false, if you are
+// only interested in the final (nonrigidly) deformed moving image
+// for example.
+(WriteResultImage "false")
+
+// The pixel type and format of the resulting deformed moving image
+(ResultImagePixelType "short")
+(ResultImageFormat "mha")
+(WriteTransformParametersEachIteration "false")
+(WriteTransformParametersEachResolution "false")
+(WriteIterationInfo "false")
+

Elastix_IMPACT_Static/Prediction.yml

@@ -4,14 +4,14 @@ Predictor:
     RegistrationNet:
       engine: elastix
       parameter_maps:
+      - Parameters_Rigid.txt
       - ParameterMap_Static.txt
       outputs_criterions: None
       max_iterations: 0
-      final_grid_spacing: 14.0
-      subset_features: 0
+      final_grid_spacing: 20.0
       spatial_samples: 2000
       parameter_overrides: []
-      resolutions:
+      levels:
         '0':
           max_iterations: 400
           models:
@@ -30,9 +30,9 @@ Predictor:
             '1':
               ref: VBoussot/impact-torchscript-models:TS/M730.pt
               voxel_size:
-              - 6.0
-              - 6.0
-              - 6.0
+              - 3.0
+              - 3.0
+              - 3.0
               layers_mask: '0000001'
               layers_weight:
               - 0.8
@@ -87,7 +87,7 @@ Predictor:
               - 2.0
               - 2.0
               - 2.0
-              layers_mask: '0000001'
+              layers_mask: '00000001'
               layers_weight:
               - 0.4
               subset_features: 64
@@ -114,13 +114,14 @@ Predictor:
               - 2.0
               - 2.0
               - 2.0
-              layers_mask: '0000001'
+              layers_mask: '00000001'
               layers_weight:
               - 0.3
               subset_features: 64
               pca: 0
               distance: Dice
       mode: Static
+      mixed_precision: true
   Dataset:
     groups_src:
       Volume_0:
@@ -178,6 +179,8 @@ Predictor:
       overlap: 20%
       pad_value: None
       extend_slice: 0
+      mode: resample
+      max_voxels: None
     subset: None
     dataset_filenames:
     - ./Dataset/:mha

Elastix_IMPACT_Static/app.json

@@ -1,7 +1,7 @@
 {
     "display_name": "elastix + IMPACT (Static), TotalSegmentator M730",
-    "short_description": "elastix B-spline driven by IMPACT on TotalSegmentator M730, last layer, Static mode: the features are extracted once on the whole image. The pairing that suits MR and CT, where the contours and the segmentation-level features carry the alignment across modalities.",
-    "description": "elastix B-spline driven by IMPACT on TotalSegmentator M730, last layer, Static mode: the features are extracted once on the whole image. The pairing that suits MR and CT, where the contours and the segmentation-level features carry the alignment across modalities.",
+    "short_description": "A rigid alignment on mutual information, then an elastix B-spline driven by IMPACT on TotalSegmentator M730 (its last decoder layer at the two coarse levels, its segmentation head at the two fine ones) and MIND, Static mode: the features are extracted once on the whole image. The pairing that suits MR and CT, where the contours and the segmentation-level features carry the alignment across modalities.",
+    "description": "A rigid alignment on mutual information, then an elastix B-spline driven by IMPACT on TotalSegmentator M730 (its last decoder layer at the two coarse levels, its segmentation head at the two fine ones) and MIND, Static mode: the features are extracted once on the whole image. The pairing that suits MR and CT, where the contours and the segmentation-level features carry the alignment across modalities.",
     "task": "registration",
     "tta": 0,
     "mc_dropout": 0,
@@ -85,5 +85,22 @@
                 }
             }
         }
-    }
-}
+    },
+    "vram_bytes_per_voxel": 150,
+    "tiling": {
+        "global": "Prediction.yml"
+    },
+    "ram_bytes_per_voxel": 950,
+    "model_files": [
+        {
+            "repo_id": "VBoussot/impact-torchscript-models",
+            "revision": "47ffad660e67cebbac8d74aecf0fa181c5dac042",
+            "filename": "MIND/R1D2_3D.pt"
+        },
+        {
+            "repo_id": "VBoussot/impact-torchscript-models",
+            "revision": "47ffad660e67cebbac8d74aecf0fa181c5dac042",
+            "filename": "TS/M730.pt"
+        }
+    ]
+}

FireANTs_Anatomix/Prediction.yml

@@ -19,35 +19,36 @@ Predictor:
       - 100
       cc_kernel: 5
       affine_metric: mi
-      affine_lr: 0.003
+      affine_lr: 0.03
       deformable_method: syn
       deformable_metric: impact
-      deformable_lr: 1.0
-      integrator_n: 10
-      smooth_warp_sigma: 0.5
+      deformable_lr: 0.5
+      smooth_warp_sigma: 1.0
       smooth_grad_sigma: 1.0
       seed: 42
       models:
         '0':
           ref: VBoussot/impact-torchscript-models:Anatomix/Anatomix.pt
           layers_mask: '1'
-          layers_weight: 1.0
+          layers_weight:
+          - 1.0
           pca: 8
-          distance: L2
+          distance: LNCC
+          feature_normalization: l2
         '1':
           ref: VBoussot/impact-torchscript-models:MIND/R1D2_3D.pt
           layers_mask: '1'
-          layers_weight: 1.0
+          layers_weight:
+          - 1.0
           pca: 6
-          distance: L1
+          distance: LNCC
+          feature_normalization: l2
       outputs_criterions: None
       mode: Static
       feature_patch: 0
       feature_chunk: 0
       feature_overlap: 0.25
-      feature_multiple: 16
-      feature_normalization: l2
-      feature_metric: cc
+      lncc_kernel: 5
   Dataset:
     groups_src:
       Volume_0:
@@ -105,6 +106,8 @@ Predictor:
       overlap: 20%
       pad_value: None
       extend_slice: 0
+      mode: resample
+      max_voxels: None
     subset: None
     dataset_filenames:
     - ./Dataset/:mha

FireANTs_Anatomix/Prediction_tile.yml

@@ -0,0 +1,141 @@
+Predictor:
+  Model:
+    classpath: impact_reg_konfai.models.fireants:RegistrationNet
+    RegistrationNet:
+      scales:
+      - 6
+      - 4
+      - 2
+      - 1
+      affine_iterations:
+      - 100
+      - 100
+      - 100
+      - 100
+      deformable_iterations:
+      - 100
+      - 100
+      - 100
+      - 100
+      cc_kernel: 5
+      affine_metric: mi
+      affine_lr: 0.03
+      deformable_method: syn
+      deformable_metric: impact
+      deformable_lr: 0.5
+      smooth_warp_sigma: 1.0
+      smooth_grad_sigma: 1.0
+      seed: 42
+      models:
+        '0':
+          ref: VBoussot/impact-torchscript-models:Anatomix/Anatomix.pt
+          layers_mask: '1'
+          layers_weight:
+          - 1.0
+          pca: 8
+          distance: LNCC
+          feature_normalization: l2
+        '1':
+          ref: VBoussot/impact-torchscript-models:MIND/R1D2_3D.pt
+          layers_mask: '1'
+          layers_weight:
+          - 1.0
+          pca: 6
+          distance: LNCC
+          feature_normalization: l2
+      outputs_criterions: None
+      mode: Static
+      feature_patch: 0
+      feature_chunk: 0
+      feature_overlap: 0.25
+      linear_method: none
+      lncc_kernel: 5
+  Dataset:
+    groups_src:
+      Volume_0:
+        groups_dest:
+          Fixed:
+            transforms:
+              TensorCast:
+                dtype: float32
+                inverse: false
+            patch_transforms: None
+            is_input: true
+      Volume_1:
+        groups_dest:
+          Moving:
+            transforms:
+              TensorCast:
+                dtype: float32
+                inverse: false
+            patch_transforms: None
+            is_input: true
+      Volume_2:
+        groups_dest:
+          FixedMask:
+            transforms:
+              TensorCast:
+                dtype: float32
+                inverse: false
+            patch_transforms: None
+            is_input: true
+      Volume_3:
+        groups_dest:
+          MovingMask:
+            transforms:
+              TensorCast:
+                dtype: float32
+                inverse: false
+            patch_transforms: None
+            is_input: true
+    augmentations:
+      DataAugmentation_0:
+        data_augmentations:
+          Flip:
+            f_prob:
+            - 0
+            - 0.5
+            - 0.5
+            vector_field: true
+            prob: 1
+        nb: 2
+    Patch:
+      patch_size:
+      - 0
+      - 0
+      - 0
+      overlap: 20%
+      pad_value: None
+      extend_slice: 0
+      mode: tile
+      max_voxels: None
+    subset: None
+    dataset_filenames:
+    - ./Dataset/:mha
+    batch_size: 1
+    num_workers: None
+    pin_memory: false
+    prefetch_factor: None
+    persistent_workers: None
+  outputs_dataset:
+    DisplacementField:
+      OutputDataset:
+        name_class: OutputDataset
+        before_reduction_transforms: None
+        after_reduction_transforms: None
+        final_transforms:
+          TensorCast:
+            dtype: float32
+            inverse: false
+        dataset_filename: Transform:itktransform
+        group: Transform
+        same_as_group: Volume_0:Fixed
+        patch_combine: Cosinus
+        reduction: Mean
+        Mean: {}
+  train_name: ImpactReg-FireANTs-Anatomix
+  manual_seed: 42
+  gpu_checkpoints: None
+  combine: Mean
+  autocast: false
+  data_log: None

FireANTs_Anatomix/app.json

@@ -85,5 +85,28 @@
                 }
             }
         }
-    }
-}
+    },
+    "vram_bytes_per_voxel": 1950,
+    "tiling": {
+        "global": "Prediction.yml",
+        "tile": "Prediction_tile.yml",
+        "tile_vram_bytes_per_voxel": 1950,
+        "tile_ram_bytes_per_voxel": 1400
+    },
+    "requirements_no_deps": [
+        "fireants>=1.5,<1.6"
+    ],
+    "ram_bytes_per_voxel": 1500,
+    "model_files": [
+        {
+            "repo_id": "VBoussot/impact-torchscript-models",
+            "revision": "47ffad660e67cebbac8d74aecf0fa181c5dac042",
+            "filename": "Anatomix/Anatomix.pt"
+        },
+        {
+            "repo_id": "VBoussot/impact-torchscript-models",
+            "revision": "47ffad660e67cebbac8d74aecf0fa181c5dac042",
+            "filename": "MIND/R1D2_3D.pt"
+        }
+    ]
+}

FireANTs_Anatomix/requirements.txt

@@ -1,4 +1,8 @@
 hydra-core
 nibabel
 pandas
+scipy
 impact_reg_konfai>=1.7.0
+matplotlib
+scikit-image
+tqdm

FireANTs_IMPACT/Prediction.yml

@@ -16,11 +16,10 @@ Predictor:
       - 50
       cc_kernel: 5
       affine_metric: mi
-      affine_lr: 0.003
+      affine_lr: 0.03
       deformable_method: syn
       deformable_metric: impact
       deformable_lr: 0.25
-      integrator_n: 10
       smooth_warp_sigma: 0.5
       smooth_grad_sigma: 1.0
       seed: 42
@@ -28,9 +27,12 @@ Predictor:
         '0':
           ref: VBoussot/impact-torchscript-models:TS/M291.pt
           layers_mask: '01'
-          layers_weight: 1.0
+          layers_weight:
+          - 1.0
           pca: 0
           distance: L1
+          feature_normalization: none
+      mode: Jacobian
       outputs_criterions: None
   Dataset:
     groups_src:
@@ -82,10 +84,15 @@ Predictor:
             prob: 1
         nb: 2
     Patch:
-      patch_size: [0, 0, 0]
+      patch_size:
+      - 0
+      - 0
+      - 0
       overlap: 20%
       pad_value: None
       extend_slice: 0
+      mode: resample
+      max_voxels: None
     subset: None
     dataset_filenames:
     - ./Dataset/:mha

FireANTs_IMPACT/Prediction_tile.yml

@@ -0,0 +1,126 @@
+Predictor:
+  Model:
+    classpath: impact_reg_konfai.models.fireants:RegistrationNet
+    RegistrationNet:
+      scales:
+      - 4
+      - 2
+      - 1
+      affine_iterations:
+      - 200
+      - 100
+      - 50
+      deformable_iterations:
+      - 200
+      - 100
+      - 50
+      cc_kernel: 5
+      affine_metric: mi
+      affine_lr: 0.03
+      deformable_method: syn
+      deformable_metric: impact
+      deformable_lr: 0.25
+      smooth_warp_sigma: 0.5
+      smooth_grad_sigma: 1.0
+      seed: 42
+      models:
+        '0':
+          ref: VBoussot/impact-torchscript-models:TS/M291.pt
+          layers_mask: '01'
+          layers_weight:
+          - 1.0
+          pca: 0
+          distance: L1
+          feature_normalization: none
+      mode: Jacobian
+      outputs_criterions: None
+      linear_method: none
+  Dataset:
+    groups_src:
+      Volume_0:
+        groups_dest:
+          Fixed:
+            transforms:
+              TensorCast:
+                dtype: float32
+                inverse: false
+            patch_transforms: None
+            is_input: true
+      Volume_1:
+        groups_dest:
+          Moving:
+            transforms:
+              TensorCast:
+                dtype: float32
+                inverse: false
+            patch_transforms: None
+            is_input: true
+      Volume_2:
+        groups_dest:
+          FixedMask:
+            transforms:
+              TensorCast:
+                dtype: float32
+                inverse: false
+            patch_transforms: None
+            is_input: true
+      Volume_3:
+        groups_dest:
+          MovingMask:
+            transforms:
+              TensorCast:
+                dtype: float32
+                inverse: false
+            patch_transforms: None
+            is_input: true
+    augmentations:
+      DataAugmentation_0:
+        data_augmentations:
+          Flip:
+            f_prob:
+            - 0
+            - 0.5
+            - 0.5
+            vector_field: true
+            prob: 1
+        nb: 2
+    Patch:
+      patch_size:
+      - 0
+      - 0
+      - 0
+      overlap: 20%
+      pad_value: None
+      extend_slice: 0
+      mode: tile
+      max_voxels: None
+    subset: None
+    dataset_filenames:
+    - ./Dataset/:mha
+    batch_size: 1
+    num_workers: None
+    pin_memory: false
+    prefetch_factor: None
+    persistent_workers: None
+  outputs_dataset:
+    DisplacementField:
+      OutputDataset:
+        name_class: OutputDataset
+        before_reduction_transforms: None
+        after_reduction_transforms: None
+        final_transforms:
+          TensorCast:
+            dtype: float32
+            inverse: false
+        dataset_filename: Transform:itktransform
+        group: Transform
+        same_as_group: Volume_0:Fixed
+        patch_combine: Cosinus
+        reduction: Mean
+        Mean: {}
+  train_name: ImpactReg-FireANTs-IMPACT
+  manual_seed: 42
+  gpu_checkpoints: None
+  combine: Mean
+  autocast: false
+  data_log: None

FireANTs_IMPACT/app.json

@@ -1,7 +1,7 @@
 {
     "display_name": "FireANTs (IMPACT)",
     "short_description": "Rigid + Affine + SyN driven by the IMPACT deep-feature metric on GPU (FireANTs).",
-    "description": "GPU deformable registration with FireANTs where the SyN stage is driven by the KonfAI IMPACT metric \u2014 deep features from one or more pretrained TorchScript models \u2014 instead of an intensity metric. A Rigid (MI) + Affine (MI) linear pre-align seeds a symmetric diffeomorphic SyN optimised with Riemannian Adam against a weighted multi-model feature distance. Produces the moved image and the total displacement field on the fixed grid. FireANTs is an external dependency under the FireANTs License v1.0 (see NOTICE); the feature models are fetched from VBoussot/impact-torchscript-models.",
+    "description": "GPU deformable registration with FireANTs where the SyN stage is driven by the KonfAI IMPACT metric — deep features from one or more pretrained TorchScript models — instead of an intensity metric. A Rigid (MI) + Affine (MI) linear pre-align seeds a symmetric diffeomorphic SyN optimised with Riemannian Adam against a weighted multi-model feature distance. Produces the displacement field on the fixed grid, from which impact-reg-konfai derives the moved image. FireANTs is an external dependency under the FireANTs License v1.0 (see NOTICE); the feature models are fetched from VBoussot/impact-torchscript-models.",
     "task": "registration",
     "tta": 0,
     "mc_dropout": 0,
@@ -85,5 +85,23 @@
                 }
             }
         }
-    }
+    },
+    "vram_bytes_per_voxel": 1150,
+    "tiling": {
+        "global": "Prediction.yml",
+        "tile": "Prediction_tile.yml",
+        "tile_vram_bytes_per_voxel": 1150,
+        "tile_ram_bytes_per_voxel": 3050
+    },
+    "requirements_no_deps": [
+        "fireants>=1.5,<1.6"
+    ],
+    "ram_bytes_per_voxel": 3150,
+    "model_files": [
+        {
+            "repo_id": "VBoussot/impact-torchscript-models",
+            "revision": "47ffad660e67cebbac8d74aecf0fa181c5dac042",
+            "filename": "TS/M291.pt"
+        }
+    ]
 }

FireANTs_IMPACT/requirements.txt

@@ -1,4 +1,8 @@
 hydra-core
 nibabel
 pandas
+scipy
 impact_reg_konfai>=1.7.0
+matplotlib
+scikit-image
+tqdm

FireANTs_IMPACT_MRCT/Evaluation_with_fid.yml

@@ -0,0 +1,22 @@
+Evaluator:
+  metrics:
+    FixedFid:
+      targets_criterions:
+        MovingFid:
+          criterions_loader:
+            TRE: {}
+  Dataset:
+    groups_src:
+      Volume_0:
+        groups_dest:
+          FixedFid:
+            transforms: None
+      Reference_0:
+        groups_dest:
+          MovingFid:
+            transforms: None
+    subset: None
+    dataset_filenames:
+    - ./Dataset:mha
+    validation: None
+  train_name: ImpactReg

FireANTs_IMPACT_MRCT/Evaluation_with_images.yml

@@ -0,0 +1,35 @@
+Evaluator:
+  metrics:
+    FixedImage:
+      targets_criterions:
+        MovingImage;Mask:
+          criterions_loader:
+            MAESaveMap:
+              reduction: mean
+              dataset: ./Evaluations/ImpactReg/Output:mha
+              group: MAE_map
+  Dataset:
+    groups_src:
+      Volume_0:
+        groups_dest:
+          FixedImage:
+            transforms: 
+              TensorCast:
+                dtype: float32
+      Reference_0:
+        groups_dest:
+          MovingImage:
+            transforms: 
+              TensorCast:
+                dtype: float32
+      Mask_0:
+        groups_dest:
+          Mask:
+            transforms:
+              TensorCast:
+                dtype: uint8
+    subset: None
+    dataset_filenames:
+    - ./Dataset:mha
+    validation: None
+  train_name: ImpactReg

FireANTs_IMPACT_MRCT/Evaluation_with_seg.yml

@@ -0,0 +1,29 @@
+Evaluator:
+  metrics:
+    FixedSeg:
+      targets_criterions:
+        MovingSeg:
+          criterions_loader:
+            DiceSaveMap:
+              labels: None
+              dataset: ./Evaluations/ImpactReg/Output:mha
+              group: Seg_MAE_map
+  Dataset:
+    groups_src:
+      Volume_0:
+        groups_dest:
+          FixedSeg:
+            transforms: 
+              TensorCast:
+                dtype: uint8
+      Reference_0:
+        groups_dest:
+          MovingSeg:
+            transforms: 
+              TensorCast:
+                dtype: uint8
+    subset: None
+    dataset_filenames:
+    - ./Dataset:mha
+    validation: None
+  train_name: ImpactReg

FireANTs_IMPACT_MRCT/NOTICE

@@ -0,0 +1,40 @@
+FireANTs_SyN — third-party attribution
+======================================
+
+This KonfAI app drives FireANTs, an external registration library. FireANTs is NOT
+redistributed here as source: the app depends on the official `fireants` wheel
+(https://pypi.org/project/fireants/), which is installed at resolve time (see
+requirements.txt) and called through its public Python API only. No FireANTs source
+code (functions, classes, or modules) is copied into this app.
+
+FireANTs is distributed under the **FireANTs License, Version 1.0 (July 2025)**, a
+custom license modified from Apache 2.0. Its redistribution clause requires that, when
+FireANTs is incorporated as a dependency in other projects, all license terms —
+including attribution and the bibliography below — be maintained.
+
+  Project : FireANTs
+  Source  : https://github.com/rohitrango/FireANTs
+  License : https://github.com/rohitrango/FireANTs/blob/main/LICENSE
+  Copyright (c) 2026 Rohit Jena. All rights reserved.
+
+Bibliography (as required by the FireANTs License — cite if you use this app)
+----------------------------------------------------------------------------
+
+  @article{jena2024fireants,
+    title={FireANTs: Adaptive Riemannian Optimization for Multi-Scale Diffeomorphic Registration},
+    author={Jena, Rohit and Chaudhari, Pratik and Gee, James C},
+    journal={Nature Communications},
+    year={2024}
+  }
+
+  @inproceedings{jena2025scalable,
+    title={A Scalable Distributed Framework for Multimodal {GigaVoxel} Image Registration},
+    author={Jena, Rohit and Zope, Vedant and Chaudhari, Pratik and Gee, James C},
+    booktitle={The Fourteenth International Conference on Learning Representations},
+    year={2026},
+    url={https://openreview.net/forum?id=8dLexnao2h}
+  }
+
+The wrapper code in this directory (Model.py, the KonfAI app configuration) is original
+work © 2025 Valentin Boussot, licensed under Apache-2.0, and is a separate work that
+merely links to the FireANTs interfaces.

FireANTs_IMPACT_MRCT/Prediction.yml

@@ -0,0 +1,137 @@
+Predictor:
+  Model:
+    classpath: impact_reg_konfai.models.fireants:RegistrationNet
+    RegistrationNet:
+      scales:
+      - 4
+      - 2
+      - 1
+      affine_iterations:
+      - 200
+      - 100
+      - 50
+      deformable_iterations:
+      - 200
+      - 100
+      - 50
+      cc_kernel: 5
+      affine_metric: mi
+      affine_lr: 0.03
+      deformable_method: syn
+      deformable_metric: impact
+      deformable_lr: 0.25
+      smooth_warp_sigma: 0.5
+      smooth_grad_sigma: 1.0
+      seed: 42
+      outputs_criterions: None
+      models:
+        '0':
+          ref: VBoussot/impact-torchscript-models:TS/M730.pt
+          layers_mask: '0000001'
+          layers_weight:
+          - 1.0
+          pca: 8
+          distance: LNCC
+          feature_normalization: l2
+        '1':
+          ref: VBoussot/impact-torchscript-models:MIND/R1D2_3D.pt
+          layers_mask: '1'
+          layers_weight:
+          - 1.0
+          pca: 6
+          distance: LNCC
+          feature_normalization: l2
+      mode: Static
+      feature_patch: 0
+      feature_chunk: 0
+      feature_overlap: 0.25
+      lncc_kernel: 5
+  Dataset:
+    groups_src:
+      Volume_0:
+        groups_dest:
+          Fixed:
+            transforms:
+              TensorCast:
+                dtype: float32
+                inverse: false
+            patch_transforms: None
+            is_input: true
+      Volume_1:
+        groups_dest:
+          Moving:
+            transforms:
+              TensorCast:
+                dtype: float32
+                inverse: false
+            patch_transforms: None
+            is_input: true
+      Volume_2:
+        groups_dest:
+          FixedMask:
+            transforms:
+              TensorCast:
+                dtype: float32
+                inverse: false
+            patch_transforms: None
+            is_input: true
+      Volume_3:
+        groups_dest:
+          MovingMask:
+            transforms:
+              TensorCast:
+                dtype: float32
+                inverse: false
+            patch_transforms: None
+            is_input: true
+    augmentations:
+      DataAugmentation_0:
+        data_augmentations:
+          Flip:
+            f_prob:
+            - 0
+            - 0.5
+            - 0.5
+            vector_field: true
+            prob: 1
+        nb: 2
+    Patch:
+      patch_size:
+      - 0
+      - 0
+      - 0
+      overlap: 20%
+      pad_value: None
+      extend_slice: 0
+      mode: resample
+      max_voxels: None
+    subset: None
+    dataset_filenames:
+    - ./Dataset/:mha
+    batch_size: 1
+    num_workers: None
+    pin_memory: false
+    prefetch_factor: None
+    persistent_workers: None
+  outputs_dataset:
+    DisplacementField:
+      OutputDataset:
+        name_class: OutputDataset
+        before_reduction_transforms: None
+        after_reduction_transforms: None
+        final_transforms:
+          TensorCast:
+            dtype: float32
+            inverse: false
+        dataset_filename: Transform:itktransform
+        group: Transform
+        same_as_group: Volume_0:Fixed
+        patch_combine: Cosinus
+        reduction: Mean
+        Mean: {}
+  train_name: ImpactReg-FireANTs-IMPACT-MRCT
+  manual_seed: 42
+  gpu_checkpoints: None
+  combine: Mean
+  autocast: false
+  data_log: None

FireANTs_IMPACT_MRCT/Prediction_tile.yml

@@ -0,0 +1,138 @@
+Predictor:
+  Model:
+    classpath: impact_reg_konfai.models.fireants:RegistrationNet
+    RegistrationNet:
+      scales:
+      - 4
+      - 2
+      - 1
+      affine_iterations:
+      - 200
+      - 100
+      - 50
+      deformable_iterations:
+      - 200
+      - 100
+      - 50
+      cc_kernel: 5
+      affine_metric: mi
+      affine_lr: 0.03
+      deformable_method: syn
+      deformable_metric: impact
+      deformable_lr: 0.25
+      smooth_warp_sigma: 0.5
+      smooth_grad_sigma: 1.0
+      seed: 42
+      outputs_criterions: None
+      linear_method: none
+      models:
+        '0':
+          ref: VBoussot/impact-torchscript-models:TS/M730.pt
+          layers_mask: '0000001'
+          layers_weight:
+          - 1.0
+          pca: 8
+          distance: LNCC
+          feature_normalization: l2
+        '1':
+          ref: VBoussot/impact-torchscript-models:MIND/R1D2_3D.pt
+          layers_mask: '1'
+          layers_weight:
+          - 1.0
+          pca: 6
+          distance: LNCC
+          feature_normalization: l2
+      mode: Static
+      feature_patch: 0
+      feature_chunk: 0
+      feature_overlap: 0.25
+      lncc_kernel: 5
+  Dataset:
+    groups_src:
+      Volume_0:
+        groups_dest:
+          Fixed:
+            transforms:
+              TensorCast:
+                dtype: float32
+                inverse: false
+            patch_transforms: None
+            is_input: true
+      Volume_1:
+        groups_dest:
+          Moving:
+            transforms:
+              TensorCast:
+                dtype: float32
+                inverse: false
+            patch_transforms: None
+            is_input: true
+      Volume_2:
+        groups_dest:
+          FixedMask:
+            transforms:
+              TensorCast:
+                dtype: float32
+                inverse: false
+            patch_transforms: None
+            is_input: true
+      Volume_3:
+        groups_dest:
+          MovingMask:
+            transforms:
+              TensorCast:
+                dtype: float32
+                inverse: false
+            patch_transforms: None
+            is_input: true
+    augmentations:
+      DataAugmentation_0:
+        data_augmentations:
+          Flip:
+            f_prob:
+            - 0
+            - 0.5
+            - 0.5
+            vector_field: true
+            prob: 1
+        nb: 2
+    Patch:
+      patch_size:
+      - 0
+      - 0
+      - 0
+      overlap: 20%
+      pad_value: None
+      extend_slice: 0
+      mode: tile
+      max_voxels: None
+    subset: None
+    dataset_filenames:
+    - ./Dataset/:mha
+    batch_size: 1
+    num_workers: None
+    pin_memory: false
+    prefetch_factor: None
+    persistent_workers: None
+  outputs_dataset:
+    DisplacementField:
+      OutputDataset:
+        name_class: OutputDataset
+        before_reduction_transforms: None
+        after_reduction_transforms: None
+        final_transforms:
+          TensorCast:
+            dtype: float32
+            inverse: false
+        dataset_filename: Transform:itktransform
+        group: Transform
+        same_as_group: Volume_0:Fixed
+        patch_combine: Cosinus
+        reduction: Mean
+        Mean: {}
+  train_name: ImpactReg-FireANTs-IMPACT-MRCT
+  manual_seed: 42
+  gpu_checkpoints: None
+  combine: Mean
+  autocast: false
+  data_log: None

FireANTs_IMPACT_MRCT/Uncertainty.yml

@@ -0,0 +1,24 @@
+Evaluator:
+  metrics:
+    Uncertainty:
+      targets_criterions:
+        None:
+          criterions_loader:
+            Mean:
+              name: Uncertainty
+  Dataset:
+    groups_src:
+      Volume_0:
+        groups_dest:
+          Uncertainty:
+            transforms:
+              Norm: {}
+              StandardDeviation: {}
+              Save:
+                dataset: ./Uncertainties/ImpactReg/Output:mha
+                group: None
+    subset: None
+    dataset_filenames:
+    - ./Dataset:mha
+    validation: None
+  train_name: ImpactReg

FireANTs_IMPACT_MRCT/app.json

@@ -0,0 +1,112 @@
+{
+    "display_name": "FireANTs SyN, TotalSegmentator MR decoder + MIND",
+    "short_description": "FireANTs_SyN with IMPACT on the last decoder layer of TotalSegmentator MR (TS/M730) and MIND, extracted once per image (Static), in place of the cross-correlation, for MR/CT.",
+    "description": "FireANTs_SyN with IMPACT on the last decoder layer of TotalSegmentator MR (TS/M730) and MIND, extracted once per image (Static), in place of the cross-correlation, for MR/CT. Everything else is FireANTs_SyN's: the rigid and affine stages on mutual information and SyN's schedule (4x2x1, 200/100/50 iterations).",
+    "task": "registration",
+    "tta": 0,
+    "mc_dropout": 0,
+    "models": [],
+    "inputs": {
+        "Fixed": {
+            "display_name": "Fixed image",
+            "volume_type": "VOLUME",
+            "required": true
+        },
+        "Moving": {
+            "display_name": "Moving image",
+            "volume_type": "VOLUME",
+            "required": true
+        },
+        "FixedMask": {
+            "display_name": "Fixed mask (optional)",
+            "volume_type": "SEGMENTATION",
+            "required": false,
+            "default": "ones"
+        },
+        "MovingMask": {
+            "display_name": "Moving mask (optional)",
+            "volume_type": "SEGMENTATION",
+            "required": false,
+            "default": "ones"
+        }
+    },
+    "outputs": {
+        "DisplacementField": {
+            "display_name": "Displacement field",
+            "volume_type": "VOLUME",
+            "required": true
+        }
+    },
+    "inputs_evaluations": {
+        "Image": {
+            "Evaluation_with_images.yml": {
+                "FixedImage": {
+                    "display_name": "Fixed image",
+                    "volume_type": "VOLUME",
+                    "required": true
+                },
+                "MovingImage": {
+                    "display_name": "Moving image",
+                    "volume_type": "VOLUME",
+                    "required": true
+                },
+                "Mask": {
+                    "display_name": "Evaluation mask",
+                    "volume_type": "SEGMENTATION",
+                    "required": false
+                }
+            }
+        },
+        "Segmentation": {
+            "Evaluation_with_seg.yml": {
+                "FixedSeg": {
+                    "display_name": "Fixed segmentation",
+                    "volume_type": "SEGMENTATION",
+                    "required": true
+                },
+                "MovingSeg": {
+                    "display_name": "Moving segmentation",
+                    "volume_type": "SEGMENTATION",
+                    "required": true
+                }
+            }
+        },
+        "Landmarks": {
+            "Evaluation_with_fid.yml": {
+                "FixedFid": {
+                    "display_name": "Fixed landmarks",
+                    "volume_type": "FIDUCIALS",
+                    "required": true
+                },
+                "MovingFid": {
+                    "display_name": "Moving landmarks",
+                    "volume_type": "FIDUCIALS",
+                    "required": true
+                }
+            }
+        }
+    },
+    "vram_bytes_per_voxel": 1950,
+    "tiling": {
+        "global": "Prediction.yml",
+        "tile": "Prediction_tile.yml",
+        "tile_vram_bytes_per_voxel": 1950,
+        "tile_ram_bytes_per_voxel": 1600
+    },
+    "requirements_no_deps": [
+        "fireants>=1.5,<1.6"
+    ],
+    "ram_bytes_per_voxel": 1700,
+    "model_files": [
+        {
+            "repo_id": "VBoussot/impact-torchscript-models",
+            "revision": "47ffad660e67cebbac8d74aecf0fa181c5dac042",
+            "filename": "TS/M730.pt"
+        },
+        {
+            "repo_id": "VBoussot/impact-torchscript-models",
+            "revision": "47ffad660e67cebbac8d74aecf0fa181c5dac042",
+            "filename": "MIND/R1D2_3D.pt"
+        }
+    ]
+}

FireANTs_IMPACT_MRCT/requirements.txt

@@ -0,0 +1,8 @@
+hydra-core
+nibabel
+pandas
+scipy
+impact_reg_konfai>=1.7.0
+matplotlib
+scikit-image
+tqdm