A preset declares its displacement field, and only that

The moved image was the required output and the field the optional one, which is
backwards: the field IS the registration, and the moved image is that field
applied to the moving -- something the orchestrator derives. Declaring both made
every preset write a second output nobody needed, and a tiled preset blend it
across every patch seam before throwing it away.

outputs_dataset now carries DisplacementField alone, and app.json marks it
required. Needs the impact-reg-konfai that derives the moved image (>=1.8.0);
an older one looks for a Moved and fails to find it.

CBCT_CT_HeadNeck/Prediction.yml

@@ -154,22 +154,6 @@ Predictor:
     prefetch_factor: None
     persistent_workers: None
   outputs_dataset:
-    MovedImage:
-      OutputDataset:
-        name_class: OutSameAsGroupDataset
-        before_reduction_transforms: None
-        after_reduction_transforms: None
-        final_transforms:
-          TensorCast:
-            dtype: float32
-            inverse: false
-        dataset_filename: Moved:mha
-        group: Moved
-        same_as_group: Volume_0:Fixed
-        patch_combine: None
-        inverse_transform: false
-        reduction: Mean
-        Mean: {}
     DisplacementField:
       OutputDataset:
         name_class: OutSameAsGroupDataset

CBCT_CT_HeadNeck/app.json

@@ -1,7 +1,7 @@
 {
     "display_name": "CBCT/CT Head&Neck",
     "short_description": "Optimized preset for CBCT/CT registration on head & neck",
-    "description": "A five-level recursive B-spline deformable registration optimized for CBCT/CT head-and-neck alignment, driven by the IMPACT metric using semantic features extracted from pretrained TotalSegmentator TorchScript models. The optimization follows a multi-resolution ASGD scheme with up to 300, 300, 200, 200, and 150 iterations and 2000 stochastic spatial samples per level. Features are extracted at progressively finer voxel scales (6 mm, 3 mm, 3 mm, 2×2×3 mm, 2×2×3 mm) using L1 distances on selected internal layers of the network. A composite objective (IMPACT + mutual information + bending energy penalty, with increased MI weight) ensures robust cross-modality alignment in complex head-and-neck anatomy while enforcing smooth, physically plausible deformations.",
+    "description": "A five-level recursive B-spline deformable registration optimized for CBCT/CT head-and-neck alignment, driven by the IMPACT metric using semantic features extracted from pretrained TotalSegmentator TorchScript models. The optimization follows a multi-resolution ASGD scheme with up to 300, 300, 200, 200, and 150 iterations and 2000 stochastic spatial samples per level. Features are extracted at progressively finer voxel scales (6 mm, 3 mm, 3 mm, 2\u00d72\u00d73 mm, 2\u00d72\u00d73 mm) using L1 distances on selected internal layers of the network. A composite objective (IMPACT + mutual information + bending energy penalty, with increased MI weight) ensures robust cross-modality alignment in complex head-and-neck anatomy while enforcing smooth, physically plausible deformations.",
     "task": "registration",
     "tta": 0,
     "mc_dropout": 0,
@@ -31,15 +31,10 @@
         }
     },
     "outputs": {
-        "MovedImage": {
-            "display_name": "Moved image",
-            "volume_type": "VOLUME",
-            "required": true
-        },
         "DisplacementField": {
             "display_name": "Displacement field",
             "volume_type": "VOLUME",
-            "required": false
+            "required": true
         }
     },
     "inputs_evaluations": {

CBCT_CT_MRSeg/Prediction.yml

@@ -187,22 +187,6 @@ Predictor:
     prefetch_factor: None
     persistent_workers: None
   outputs_dataset:
-    MovedImage:
-      OutputDataset:
-        name_class: OutSameAsGroupDataset
-        before_reduction_transforms: None
-        after_reduction_transforms: None
-        final_transforms:
-          TensorCast:
-            dtype: float32
-            inverse: false
-        dataset_filename: Moved:mha
-        group: Moved
-        same_as_group: Volume_0:Fixed
-        patch_combine: None
-        inverse_transform: false
-        reduction: Mean
-        Mean: {}
     DisplacementField:
       OutputDataset:
         name_class: OutSameAsGroupDataset

CBCT_CT_MRSeg/app.json

@@ -1,7 +1,7 @@
 {
     "display_name": "CBCT/CT preset with MRSegmentator",
     "short_description": "Generic CBCT/CT deformable registration using MRSegmentator features",
-    "description": "A four-level recursive B-spline deformable registration optimized for generic CBCT/CT alignment, driven by the IMPACT metric using semantic features extracted from the pretrained MRSegmentator model. The scheme follows a multi-resolution strategy with up to 300, 300, 250, and 200 ASGD iterations and 2000 stochastic spatial samples per level. Features are extracted at progressively finer voxel scales (3 mm, 3 mm, 2×2×3 mm, 2×2×3 mm), with a level-dependent combination of Dice-based segmentation overlap and L1 feature distances on selected internal layers of MRSegmentator. Early levels rely on pure Dice supervision, while finer stages progressively integrate feature-level alignment with increasing L1 contribution (0.3/0.7, 0.5/0.5) and a final purely feature-based stage. The optimization minimizes a composite objective (IMPACT + mutual information + bending energy penalty), enabling robust cross-modality alignment between CBCT and CT while enforcing smooth, physically plausible deformations.",
+    "description": "A four-level recursive B-spline deformable registration optimized for generic CBCT/CT alignment, driven by the IMPACT metric using semantic features extracted from the pretrained MRSegmentator model. The scheme follows a multi-resolution strategy with up to 300, 300, 250, and 200 ASGD iterations and 2000 stochastic spatial samples per level. Features are extracted at progressively finer voxel scales (3 mm, 3 mm, 2\u00d72\u00d73 mm, 2\u00d72\u00d73 mm), with a level-dependent combination of Dice-based segmentation overlap and L1 feature distances on selected internal layers of MRSegmentator. Early levels rely on pure Dice supervision, while finer stages progressively integrate feature-level alignment with increasing L1 contribution (0.3/0.7, 0.5/0.5) and a final purely feature-based stage. The optimization minimizes a composite objective (IMPACT + mutual information + bending energy penalty), enabling robust cross-modality alignment between CBCT and CT while enforcing smooth, physically plausible deformations.",
     "task": "registration",
     "tta": 0,
     "mc_dropout": 0,
@@ -31,15 +31,10 @@
         }
     },
     "outputs": {
-        "MovedImage": {
-            "display_name": "Moved image",
-            "volume_type": "VOLUME",
-            "required": true
-        },
         "DisplacementField": {
             "display_name": "Displacement field",
             "volume_type": "VOLUME",
-            "required": false
+            "required": true
         }
     },
     "inputs_evaluations": {

ConvexAdam_Coarse/Prediction.yml

@@ -94,22 +94,6 @@ Predictor:
     prefetch_factor: None
     persistent_workers: None
   outputs_dataset:
-    MovedImage:
-      OutputDataset:
-        name_class: OutSameAsGroupDataset
-        before_reduction_transforms: None
-        after_reduction_transforms: None
-        final_transforms:
-          TensorCast:
-            dtype: float32
-            inverse: false
-        dataset_filename: Moved:mha
-        group: Moved
-        same_as_group: Volume_0:Fixed
-        patch_combine: None
-        inverse_transform: false
-        reduction: Mean
-        Mean: {}
     DisplacementField:
       OutputDataset:
         name_class: OutSameAsGroupDataset

ConvexAdam_Coarse/app.json

@@ -31,15 +31,10 @@
         }
     },
     "outputs": {
-        "MovedImage": {
-            "display_name": "Moved image",
-            "volume_type": "VOLUME",
-            "required": true
-        },
         "DisplacementField": {
             "display_name": "Displacement field",
             "volume_type": "VOLUME",
-            "required": false
+            "required": true
         }
     },
     "inputs_evaluations": {

ConvexAdam_Composite/Prediction.yml

@@ -95,22 +95,6 @@ Predictor:
     prefetch_factor: None
     persistent_workers: None
   outputs_dataset:
-    MovedImage:
-      OutputDataset:
-        name_class: OutSameAsGroupDataset
-        before_reduction_transforms: None
-        after_reduction_transforms: None
-        final_transforms:
-          TensorCast:
-            dtype: float32
-            inverse: false
-        dataset_filename: Moved:mha
-        group: Moved
-        same_as_group: Volume_0:Fixed
-        patch_combine: None
-        inverse_transform: false
-        reduction: Mean
-        Mean: {}
     DisplacementField:
       OutputDataset:
         name_class: OutSameAsGroupDataset

ConvexAdam_Composite/app.json

@@ -31,15 +31,10 @@
         }
     },
     "outputs": {
-        "MovedImage": {
-            "display_name": "Moved image",
-            "volume_type": "VOLUME",
-            "required": true
-        },
         "DisplacementField": {
             "display_name": "Displacement field",
             "volume_type": "VOLUME",
-            "required": false
+            "required": true
         }
     },
     "inputs_evaluations": {

ConvexAdam_Fine/Prediction.yml

@@ -94,22 +94,6 @@ Predictor:
     prefetch_factor: None
     persistent_workers: None
   outputs_dataset:
-    MovedImage:
-      OutputDataset:
-        name_class: OutSameAsGroupDataset
-        before_reduction_transforms: None
-        after_reduction_transforms: None
-        final_transforms:
-          TensorCast:
-            dtype: float32
-            inverse: false
-        dataset_filename: Moved:mha
-        group: Moved
-        same_as_group: Volume_0:Fixed
-        patch_combine: None
-        inverse_transform: false
-        reduction: Mean
-        Mean: {}
     DisplacementField:
       OutputDataset:
         name_class: OutSameAsGroupDataset

ConvexAdam_Fine/app.json

@@ -65,15 +65,10 @@
         }
     },
     "outputs": {
-        "MovedImage": {
-            "display_name": "Moved image",
-            "volume_type": "VOLUME",
-            "required": true
-        },
         "DisplacementField": {
             "display_name": "Displacement field",
             "volume_type": "VOLUME",
-            "required": false
+            "required": true
         }
     },
     "inputs_evaluations": {

FireANTs_Affine/Prediction.yml

@@ -91,22 +91,6 @@ Predictor:
     prefetch_factor: None
     persistent_workers: None
   outputs_dataset:
-    MovedImage:
-      OutputDataset:
-        name_class: OutSameAsGroupDataset
-        before_reduction_transforms: None
-        after_reduction_transforms: None
-        final_transforms:
-          TensorCast:
-            dtype: float32
-            inverse: false
-        dataset_filename: Moved:mha
-        group: Moved
-        same_as_group: Volume_0:Fixed
-        patch_combine: None
-        inverse_transform: false
-        reduction: Mean
-        Mean: {}
     DisplacementField:
       OutputDataset:
         name_class: OutSameAsGroupDataset

FireANTs_Affine/app.json

@@ -1,7 +1,7 @@
 {
     "display_name": "FireANTs (Affine)",
     "short_description": "Rigid + Affine linear alignment on GPU (FireANTs), no deformable stage.",
-    "description": "GPU linear registration with FireANTs: a Rigid (MI, centre-of-mass init) then Affine (MI) alignment optimised with Riemannian Adam, with no deformable stage. Produces the moved image and the affine displacement field on the fixed grid — use it on its own, or as a linear pre-align feeding a deformable preset. FireANTs is an external dependency under the FireANTs License v1.0 (see NOTICE).",
+    "description": "GPU linear registration with FireANTs: a Rigid (MI, centre-of-mass init) then Affine (MI) alignment optimised with Riemannian Adam, with no deformable stage. Produces the moved image and the affine displacement field on the fixed grid \u2014 use it on its own, or as a linear pre-align feeding a deformable preset. FireANTs is an external dependency under the FireANTs License v1.0 (see NOTICE).",
     "task": "registration",
     "tta": 0,
     "mc_dropout": 0,
@@ -31,15 +31,10 @@
         }
     },
     "outputs": {
-        "MovedImage": {
-            "display_name": "Moved image",
-            "volume_type": "VOLUME",
-            "required": true
-        },
         "DisplacementField": {
             "display_name": "Displacement field",
             "volume_type": "VOLUME",
-            "required": false
+            "required": true
         }
     },
     "inputs_evaluations": {

FireANTs_IMPACT/Prediction.yml

@@ -98,22 +98,6 @@ Predictor:
     prefetch_factor: None
     persistent_workers: None
   outputs_dataset:
-    MovedImage:
-      OutputDataset:
-        name_class: OutSameAsGroupDataset
-        before_reduction_transforms: None
-        after_reduction_transforms: None
-        final_transforms:
-          TensorCast:
-            dtype: float32
-            inverse: false
-        dataset_filename: Moved:mha
-        group: Moved
-        same_as_group: Volume_0:Fixed
-        patch_combine: None
-        inverse_transform: false
-        reduction: Mean
-        Mean: {}
     DisplacementField:
       OutputDataset:
         name_class: OutSameAsGroupDataset

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 — 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 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 \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.",
     "task": "registration",
     "tta": 0,
     "mc_dropout": 0,
@@ -31,15 +31,10 @@
         }
     },
     "outputs": {
-        "MovedImage": {
-            "display_name": "Moved image",
-            "volume_type": "VOLUME",
-            "required": true
-        },
         "DisplacementField": {
             "display_name": "Displacement field",
             "volume_type": "VOLUME",
-            "required": false
+            "required": true
         }
     },
     "inputs_evaluations": {

FireANTs_SyN/Prediction.yml

@@ -91,22 +91,6 @@ Predictor:
     prefetch_factor: None
     persistent_workers: None
   outputs_dataset:
-    MovedImage:
-      OutputDataset:
-        name_class: OutSameAsGroupDataset
-        before_reduction_transforms: None
-        after_reduction_transforms: None
-        final_transforms:
-          TensorCast:
-            dtype: float32
-            inverse: false
-        dataset_filename: Moved:mha
-        group: Moved
-        same_as_group: Volume_0:Fixed
-        patch_combine: None
-        inverse_transform: false
-        reduction: Mean
-        Mean: {}
     DisplacementField:
       OutputDataset:
         name_class: OutSameAsGroupDataset

FireANTs_SyN/app.json

@@ -31,15 +31,10 @@
         }
     },
     "outputs": {
-        "MovedImage": {
-            "display_name": "Moved image",
-            "volume_type": "VOLUME",
-            "required": true
-        },
         "DisplacementField": {
             "display_name": "Displacement field",
             "volume_type": "VOLUME",
-            "required": false
+            "required": true
         }
     },
     "inputs_evaluations": {

Generic_Rigid/Prediction.yml

@@ -75,22 +75,6 @@ Predictor:
     prefetch_factor: None
     persistent_workers: None
   outputs_dataset:
-    MovedImage:
-      OutputDataset:
-        name_class: OutSameAsGroupDataset
-        before_reduction_transforms: None
-        after_reduction_transforms: None
-        final_transforms:
-          TensorCast:
-            dtype: float32
-            inverse: false
-        dataset_filename: Moved:mha
-        group: Moved
-        same_as_group: Volume_0:Fixed
-        patch_combine: None
-        inverse_transform: false
-        reduction: Mean
-        Mean: {}
     DisplacementField:
       OutputDataset:
         name_class: OutSameAsGroupDataset

Generic_Rigid/app.json

@@ -31,15 +31,10 @@
         }
     },
     "outputs": {
-        "MovedImage": {
-            "display_name": "Moved image",
-            "volume_type": "VOLUME",
-            "required": true
-        },
         "DisplacementField": {
             "display_name": "Displacement field",
             "volume_type": "VOLUME",
-            "required": false
+            "required": true
         }
     },
     "inputs_evaluations": {

Generic_Rigid_BSpline/Prediction.yml

@@ -77,22 +77,6 @@ Predictor:
     prefetch_factor: None
     persistent_workers: None
   outputs_dataset:
-    MovedImage:
-      OutputDataset:
-        name_class: OutSameAsGroupDataset
-        before_reduction_transforms: None
-        after_reduction_transforms: None
-        final_transforms:
-          TensorCast:
-            dtype: float32
-            inverse: false
-        dataset_filename: Moved:mha
-        group: Moved
-        same_as_group: Volume_0:Fixed
-        patch_combine: None
-        inverse_transform: false
-        reduction: Mean
-        Mean: {}
     DisplacementField:
       OutputDataset:
         name_class: OutSameAsGroupDataset

Generic_Rigid_BSpline/app.json

@@ -31,15 +31,10 @@
         }
     },
     "outputs": {
-        "MovedImage": {
-            "display_name": "Moved image",
-            "volume_type": "VOLUME",
-            "required": true
-        },
         "DisplacementField": {
             "display_name": "Displacement field",
             "volume_type": "VOLUME",
-            "required": false
+            "required": true
         }
     },
     "inputs_evaluations": {

MR_CT_HeadNeck/Prediction.yml

@@ -139,22 +139,6 @@ Predictor:
     prefetch_factor: None
     persistent_workers: None
   outputs_dataset:
-    MovedImage:
-      OutputDataset:
-        name_class: OutSameAsGroupDataset
-        before_reduction_transforms: None
-        after_reduction_transforms: None
-        final_transforms:
-          TensorCast:
-            dtype: float32
-            inverse: false
-        dataset_filename: Moved:mha
-        group: Moved
-        same_as_group: Volume_0:Fixed
-        patch_combine: None
-        inverse_transform: false
-        reduction: Mean
-        Mean: {}
     DisplacementField:
       OutputDataset:
         name_class: OutSameAsGroupDataset

MR_CT_HeadNeck/app.json

@@ -31,15 +31,10 @@
         }
     },
     "outputs": {
-        "MovedImage": {
-            "display_name": "Moved image",
-            "volume_type": "VOLUME",
-            "required": true
-        },
         "DisplacementField": {
             "display_name": "Displacement field",
             "volume_type": "VOLUME",
-            "required": false
+            "required": true
         }
     },
     "inputs_evaluations": {

MR_CT_MRSeg/Prediction.yml

@@ -187,22 +187,6 @@ Predictor:
     prefetch_factor: None
     persistent_workers: None
   outputs_dataset:
-    MovedImage:
-      OutputDataset:
-        name_class: OutSameAsGroupDataset
-        before_reduction_transforms: None
-        after_reduction_transforms: None
-        final_transforms:
-          TensorCast:
-            dtype: float32
-            inverse: false
-        dataset_filename: Moved:mha
-        group: Moved
-        same_as_group: Volume_0:Fixed
-        patch_combine: None
-        inverse_transform: false
-        reduction: Mean
-        Mean: {}
     DisplacementField:
       OutputDataset:
         name_class: OutSameAsGroupDataset

MR_CT_MRSeg/app.json

@@ -31,15 +31,10 @@
         }
     },
     "outputs": {
-        "MovedImage": {
-            "display_name": "Moved image",
-            "volume_type": "VOLUME",
-            "required": true
-        },
         "DisplacementField": {
             "display_name": "Displacement field",
             "volume_type": "VOLUME",
-            "required": false
+            "required": true
         }
     },
     "inputs_evaluations": {

MR_CT_TS/Prediction.yml

@@ -187,22 +187,6 @@ Predictor:
     prefetch_factor: None
     persistent_workers: None
   outputs_dataset:
-    MovedImage:
-      OutputDataset:
-        name_class: OutSameAsGroupDataset
-        before_reduction_transforms: None
-        after_reduction_transforms: None
-        final_transforms:
-          TensorCast:
-            dtype: float32
-            inverse: false
-        dataset_filename: Moved:mha
-        group: Moved
-        same_as_group: Volume_0:Fixed
-        patch_combine: None
-        inverse_transform: false
-        reduction: Mean
-        Mean: {}
     DisplacementField:
       OutputDataset:
         name_class: OutSameAsGroupDataset

MR_CT_TS/app.json

@@ -31,15 +31,10 @@
         }
     },
     "outputs": {
-        "MovedImage": {
-            "display_name": "Moved image",
-            "volume_type": "VOLUME",
-            "required": true
-        },
         "DisplacementField": {
             "display_name": "Displacement field",
             "volume_type": "VOLUME",
-            "required": false
+            "required": true
         }
     },
     "inputs_evaluations": {