Add verified SimCortex v2 pretrained model archive

zenodo-v2/MODEL_CARD.md

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+# SimCortex v2 Model Card
+
+## Model overview
+
+SimCortex v2 is a deep-learning pipeline for reconstructing four cortical surfaces from T1-weighted structural MRI:
+
+- left pial surface
+- left white-matter surface
+- right pial surface
+- right white-matter surface
+
+The pipeline operates in MNI152 space and combines volumetric segmentation, cortical-surface initialization, and simultaneous deformation of the four cortical surfaces.
+
+## Intended use
+
+The released models are intended for research use in cortical surface reconstruction and downstream morphometric analysis.
+
+They are not intended for standalone clinical diagnosis or treatment decisions.
+
+## Pipeline stages
+
+1. T1-weighted MRI preprocessing into MNI152 space.
+2. Nine-class 3D U-Net segmentation.
+3. Initial cortical-surface generation.
+4. Simultaneous deformation of left/right white and pial surfaces.
+
+## Released checkpoints
+
+### Segmentation
+
+File:
+
+`seg/seg_best_dice.pt`
+
+Role:
+
+Final segmentation checkpoint used by the released pipeline.
+
+SHA256:
+
+`2cea6dc1606958dbdb2aea50748b73ff73e604b0c367b3b1588cef7a112c8e06`
+
+### Primary deformation checkpoint
+
+File:
+
+`deform/deform_best_rmse.pth`
+
+Role:
+
+Recommended deformation checkpoint used for the final SimCortex v2 paper evaluation.
+
+SHA256:
+
+`3fb84c917953e479e72d59291837bd6b08f40fb197534046b95dc5a452e86b95`
+
+### Secondary deformation checkpoint
+
+File:
+
+`deform/deform_best_model.pth`
+
+Role:
+
+Alternative deformation checkpoint retained for reproducibility and comparison.
+
+SHA256:
+
+`d30d3218069a6eb395dacd3ff0dd085a93f6f0102616eed809b90c362b885b40`
+
+## Model file format
+
+The released `.pt` and `.pth` files are PyTorch state dictionaries intended for inference.
+
+Training-resume checkpoints, optimizer states, and scheduler states are not included.
+
+## Training data split
+
+The released training split contains 515 subjects from HCP-YA and OASIS-1:
+
+- training: 361
+- validation: 77
+- test: 77
+
+By dataset:
+
+HCP-YA:
+- 70 train
+- 15 validation
+- 15 test
+- 100 total
+
+OASIS-1:
+- 291 train
+- 62 validation
+- 62 test
+- 415 total
+
+The exact split is stored in:
+
+`splits/dataset_split.csv`
+
+SHA256:
+
+`68f42ef3ed09373685de5d1dd144c7d3d72b7f8083850057dcccd5780756188d`
+
+## Evaluation cohort
+
+The public evaluation cohort definition is stored in:
+
+`splits/evaluation_sample40.csv`
+
+It contains:
+
+- 560 cases
+- 14 datasets
+- 40 cases per dataset
+
+SHA256:
+
+`2c41b21afea327756c8d7fccc30bd03e461670d59dc00f941e8cba06fcf59842`
+
+## Configuration files
+
+The archive includes the YAML configurations used by the released pipeline:
+
+- `configs/seg/train.yaml`
+- `configs/seg/inference.yaml`
+- `configs/seg/eval.yaml`
+- `configs/initsurf/generate.yaml`
+- `configs/deform/train.yaml`
+- `configs/deform/inference.yaml`
+- `configs/deform/eval.yaml`
+
+## Surface ordering
+
+The deformation implementation uses the following four-surface order:
+
+```text
+lh_pial
+lh_white
+rh_pial
+rh_white
+```
+
+## Input and output
+
+Input:
+
+T1-weighted MRI processed into the reference space expected by the SimCortex pipeline.
+
+Output:
+
+Left/right white-matter and pial cortical surface meshes.
+
+## Data availability
+
+The MRI datasets themselves are not included in this model archive.
+
+The associated dataset release is hosted separately in the Federated Research Data Repository (FRDR).
+
+FRDR dataset DOI:
+
+`10.20383/103.01769`
+
+## Limitations
+
+The released models were developed and evaluated using the datasets and processing conventions described in the SimCortex v2 study.
+
+Performance may vary for data acquired with different scanners, protocols, populations, preprocessing pipelines, or image quality.
+
+The models are provided for research use and should be independently validated before use in new settings.
+
+## Reproducibility
+
+The archive includes:
+
+- pretrained model state dictionaries
+- frozen YAML configurations
+- training/validation/test split
+- final evaluation cohort definition
+- provenance metadata
+- SHA256 checksums
+
+The source-code repository should be used together with this archive for inference and reproduction of the released pipeline.

zenodo-v2/README.md

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+# SimCortex v2: Pre-trained Models and Reproducibility Files
+
+This archive contains the finalized pre-trained model weights and reproducibility files for SimCortex v2, a deep-learning pipeline for simultaneous reconstruction of left/right white-matter and pial cortical surfaces from T1-weighted MRI.
+
+The archive contains inference-ready PyTorch state dictionaries, configuration files, the training/validation/test split used for model development, and the evaluation cohort definition used for the final benchmark.
+
+## Recommended checkpoint
+
+The primary deformation checkpoint is:
+
+`deform/deform_best_rmse.pth`
+
+This is the recommended checkpoint and the one used for the final SimCortex v2 paper evaluation.
+
+The archive also includes:
+
+`deform/deform_best_model.pth`
+
+as a secondary checkpoint retained for reproducibility and comparison.
+
+The segmentation checkpoint is:
+
+`seg/seg_best_dice.pt`
+
+## Archive contents
+
+```text
+SimCortex_v2_pretrained_models/
+├── README.md
+├── MODEL_CARD.md
+├── provenance.json
+├── SHA256SUMS
+├── configs/
+│   ├── deform/
+│   │   ├── eval.yaml
+│   │   ├── inference.yaml
+│   │   └── train.yaml
+│   ├── initsurf/
+│   │   └── generate.yaml
+│   └── seg/
+│       ├── eval.yaml
+│       ├── inference.yaml
+│       └── train.yaml
+├── deform/
+│   ├── deform_best_model.pth
+│   └── deform_best_rmse.pth
+├── seg/
+│   └── seg_best_dice.pt
+└── splits/
+    ├── dataset_split.csv
+    └── evaluation_sample40.csv
+```
+
+## Model weights
+
+### Segmentation
+
+`seg/seg_best_dice.pt`
+
+Pre-trained weights for the 3D U-Net segmentation stage. The network predicts nine classes used by the subsequent cortical-surface initialization stage.
+
+### Deformation
+
+`deform/deform_best_rmse.pth`
+
+Primary and recommended deformation checkpoint.
+
+`deform/deform_best_model.pth`
+
+Secondary deformation checkpoint retained for reproducibility and comparison.
+
+The released `.pt` and `.pth` files contain model state dictionaries intended for inference. Optimizer state and training-resume checkpoints are not included.
+
+## Data splits
+
+`splits/dataset_split.csv` contains the HCP-YA and OASIS-1 subject split used for model development:
+
+- 515 subjects total
+- 361 training subjects
+- 77 validation subjects
+- 77 test subjects
+
+Dataset composition:
+
+- HCP-YA: 100 subjects
+- OASIS-1: 415 subjects
+
+`splits/evaluation_sample40.csv` defines the final evaluation cohort:
+
+- 560 cases
+- 14 datasets
+- 40 cases per dataset
+
+The evaluation cohort file contains only public case identifiers and does not contain workstation-specific paths.
+
+## Configuration files
+
+The `configs/` directory contains the frozen YAML configuration files associated with the released pipeline:
+
+- segmentation training, inference, and evaluation
+- initial-surface generation
+- deformation training, inference, and evaluation
+
+These files are also maintained in the SimCortex source-code repository.
+
+## Pipeline
+
+The released model corresponds to the following processing stages:
+
+1. preprocessing of T1-weighted MRI into MNI152 space;
+2. nine-class 3D U-Net segmentation;
+3. initialization of left/right white and pial cortical surfaces;
+4. simultaneous deformation of the four cortical surfaces.
+
+The deformation stage reconstructs the following four surfaces:
+
+```text
+lh_pial
+lh_white
+rh_pial
+rh_white
+```
+
+## Reference-space data
+
+The MNI152 template itself is not redistributed in this archive.
+
+Users should obtain the required reference-space resources through the software dependencies or sources documented by the SimCortex code repository.
+
+## Dataset availability
+
+The MRI datasets and derived neuroimaging data are not redistributed in this model archive.
+
+The associated SimCortex dataset release is archived separately in the Federated Research Data Repository (FRDR).
+
+FRDR dataset DOI:
+
+`10.20383/103.01769`
+
+## File integrity
+
+SHA256 checksums for the released files are provided in:
+
+`SHA256SUMS`
+
+Additional checkpoint and cohort provenance is recorded in:
+
+`provenance.json`
+
+## Citation
+
+Please cite the SimCortex v2 paper and the corresponding Zenodo release when using these pretrained models.
+
+The final publication DOI and Zenodo DOI should be used once available.

zenodo-v2/SHA256SUMS

@@ -0,0 +1,15 @@
+313db997385b99713dd6f4ac0205c9acda554e8296283509eaf8179bdba4e1ea  ./configs/deform/eval.yaml
+9abc2a219d7cf9195b27023c509061fda1a04ec90aac0da05283f0898fd85005  ./configs/deform/inference.yaml
+56fc16adfadc736e237d6725f2e5d39e0288c487b1edcd4c4a72f5fb7e2b3245  ./configs/deform/train.yaml
+4b3aa735bc976b5dba6fd646447cdeb9b780893302c9a447099ab9095b14f73a  ./configs/initsurf/generate.yaml
+9079a8bb871dfbd9416bf506b4846c9e7d2eb418033b6e57f61b28379226b2d1  ./configs/seg/eval.yaml
+5da1b229cd3e215b8f0f7df4754a3871744edfa89a0b34802a5f612a0192afe9  ./configs/seg/inference.yaml
+1f88a05aea524325c9be5286d43cea9de478e260512e4413f7c6e982a6ab19fb  ./configs/seg/train.yaml
+d30d3218069a6eb395dacd3ff0dd085a93f6f0102616eed809b90c362b885b40  ./deform/deform_best_model.pth
+3fb84c917953e479e72d59291837bd6b08f40fb197534046b95dc5a452e86b95  ./deform/deform_best_rmse.pth
+afaf0741348a43709d272d9296eda7feccb41a7dc8bb2ed0de04e8562fc8e45b  ./MODEL_CARD.md
+6ec06384e95c1a25fa46e699d456b3d5fc2ab6f9b8eb2ae891c8e8f5f48c261b  ./provenance.json
+a6c77cc0c2a9dc070519330971e3bbbf2a3655d3fffb2ababa70e6d61d3c3705  ./README.md
+2cea6dc1606958dbdb2aea50748b73ff73e604b0c367b3b1588cef7a112c8e06  ./seg/seg_best_dice.pt
+68f42ef3ed09373685de5d1dd144c7d3d72b7f8083850057dcccd5780756188d  ./splits/dataset_split.csv
+2c41b21afea327756c8d7fccc30bd03e461670d59dc00f941e8cba06fcf59842  ./splits/evaluation_sample40.csv

zenodo-v2/configs/deform/eval.yaml

@@ -0,0 +1,39 @@
+user_config: null
+
+dataset:
+  path: null
+
+  split_file: /path/to/datasets/splits/dataset_split.csv
+  split_name: test
+  session_label: "01"
+  space: "MNI152"
+
+  # Multi-dataset mode.
+  roots:
+    HCP_YA: /path/to/datasets/hcpya-u100/derivatives/sc-preproc
+    OASIS1: /path/to/datasets/oasis-1/derivatives/sc-preproc
+
+outputs:
+  pred_root: null
+
+  # Multi-dataset mode predictions.
+  pred_roots:
+    HCP_YA: /path/to/datasets/hcpya-u100/derivatives/sc-deform
+    OASIS1: /path/to/datasets/oasis-1/derivatives/sc-deform
+
+  out_dir: /path/to/simcortex-runs/deform/exp01_hcpya+oasis1/eval
+
+eval:
+  seed: 1234
+  pred_desc: "deform"
+  device: "cuda:0"
+  n_chamfer: 150000
+  n_assd_hd: 150000
+  log_level: "INFO"
+
+hydra:
+  run:
+    dir: ${outputs.out_dir}
+  output_subdir: null
+  job:
+    chdir: false

zenodo-v2/configs/deform/inference.yaml

@@ -0,0 +1,55 @@
+user_config: null
+
+dataset:
+  path: null
+  initsurf_root: null
+
+  split_file: /path/to/datasets/splits/dataset_split.csv
+  split_name: test
+  session_label: "01"
+  space: "MNI152"
+
+  # Multi-dataset mode.
+  roots:
+    HCP_YA: /path/to/datasets/hcpya-u100/derivatives/sc-preproc
+    OASIS1: /path/to/datasets/oasis-1/derivatives/sc-preproc
+
+  initsurf_roots:
+    HCP_YA: /path/to/datasets/hcpya-u100/derivatives/sc-initsurf
+    OASIS1: /path/to/datasets/oasis-1/derivatives/sc-initsurf
+
+  surface_name: ["lh_pial", "lh_white", "rh_pial", "rh_white"]
+  prob_clip_min: 0.0
+  prob_clip_max: 1.0
+  prob_gamma: 1.0
+  add_prob_grad: false
+
+inference:
+  device: "cuda:0"
+  batch_size: 1
+  num_workers: 2
+  log_level: "INFO"
+  overwrite: true
+
+model:
+  ckpt_path: /path/to/deform_best_rmse.pth
+  strict_load: true
+  c_in: 2
+  sigma: 1
+  n_steps: 8
+  inshape: [184, 224, 184]
+  c_hid: [8, 16, 32, 64, 128, 128]
+  geom_ratio: 0.5
+  geom_depth: 6
+  gn_groups: 8
+  gate_init: -3.0
+
+outputs:
+  out_root: null
+
+  # Multi-dataset mode outputs.
+  out_roots:
+    HCP_YA: /path/to/datasets/hcpya-u100/derivatives/sc-deform
+    OASIS1: /path/to/datasets/oasis-1/derivatives/sc-deform
+
+  log_dir: /path/to/simcortex-runs/deform/exp01_hcpya+oasis1/logs_infer

zenodo-v2/configs/deform/train.yaml

@@ -0,0 +1,118 @@
+user_config: null
+
+dataset:
+  split_file: /path/to/datasets/splits/dataset_split.csv
+  train_split_name: train
+  val_split_name: val
+  session_label: '01'
+  space: MNI152
+  roots:
+    HCP_YA: /path/to/datasets/hcpya-u100/derivatives/sc-preproc
+    OASIS1: /path/to/datasets/oasis-1/derivatives/sc-preproc
+  initsurf_roots:
+    HCP_YA: /path/to/datasets/hcpya-u100/derivatives/sc-initsurf
+    OASIS1: /path/to/datasets/oasis-1/derivatives/sc-initsurf
+  surface_name:
+    - lh_pial
+    - lh_white
+    - rh_pial
+    - rh_white
+  prob_clip_min: 0.0
+  prob_clip_max: 1.0
+  prob_gamma: 1.0
+
+  aug_prob: 0.3
+  aug_rot_range_deg: 3.0
+  aug_scale_range: 0.02
+  aug_trans_range_mm: 1.0
+
+  aug_intensity_prob: 0.3
+  aug_bias_strength: 0.2
+  aug_gain_range: 0.1
+  aug_bright_range: 0.1
+  aug_noise_std: 0.05
+
+trainer:
+  seed: 2025
+  img_batch_size: 1
+  grad_accum_steps: 4
+  num_epochs: 600
+  validation_interval: 5
+  collision_interval: 5
+
+  learning_rate: 1.0e-4
+  weight_decay: 1.0e-4
+
+  points_per_image: 180000
+  val_points_per_image: 150000 
+
+  num_workers: 4
+  log_level: INFO
+  mesh_chunk: 4
+  grad_clip_norm: 1.0
+
+  scheduler_patience: 4
+  scheduler_factor: 0.5
+  scheduler_min_lr: 1.0e-6
+  scheduler_threshold_mm: 0.0004
+  scheduler_threshold_mode: abs
+  scheduler_cooldown: 1
+
+  early_stop_patience: 15
+  early_stop_min_delta_mm: 0.0003
+  resume_from: null
+
+model:
+  sigma: 1
+  n_steps: 8
+  inshape:
+    - 184
+    - 224
+    - 184
+  c_hid:
+    - 8
+    - 16
+    - 32
+    - 64
+    - 128
+    - 128
+  c_in: 2
+  geom_ratio: 0.5
+  geom_depth: 6
+  gn_groups: 8
+  gate_init: -3.0
+  dropout: 0.1
+  init_ckpt: null
+  init_strict: true
+
+objective:
+  chamfer_weight: 1.0
+  chamfer_scale: 1.0
+
+  edge_loss_weight: 2.5
+  normal_weight: 0.25
+  reg_warmup_epochs: 25
+
+  hd_weight: 5.5
+  hd_p: 0.05
+  hd_lambda_mm: 0.75
+  hd_points: 50000
+
+  signed_nested_weight: 8.0
+  signed_margin_mm: 0.55
+  signed_points: 50000
+
+  pial_lr_hd_weight: 1.5
+  pial_lr_hd_p: 0.05
+  pial_lr_hd_lambda_mm: 1.0
+  pial_lr_hd_points: 30000
+
+checkpoint:
+  alpha_wp: 0.03
+  alpha_lr: 0.015
+  rmse_guardrail_rel: 1.03
+  min_delta_score: 0.0001
+  require_collision_for_best: true
+
+outputs:
+  root: /path/to/simcortex-runs/deform/exp01_hcpya+oasis1

zenodo-v2/configs/initsurf/generate.yaml

@@ -0,0 +1,58 @@
+# SimCortex InitSurf generation config
+
+n_workers: 4
+
+dataset:
+  path: null
+  seg_root: null
+
+  split_file: /path/to/datasets/splits/dataset_split.csv
+  split_name: all
+  session_label: "01"
+  space: "MNI152"
+
+  # Multi-dataset mode.
+  roots:
+    HCP_YA: /path/to/datasets/hcpya-u100/derivatives/sc-preproc
+    OASIS1: /path/to/datasets/oasis-1/derivatives/sc-preproc
+
+  seg_roots:
+    HCP_YA: /path/to/datasets/hcpya-u100/derivatives/sc-seg
+    OASIS1: /path/to/datasets/oasis-1/derivatives/sc-seg
+
+outputs:
+  out_root: null
+
+  # Multi-dataset mode outputs.
+  out_roots:
+    HCP_YA: /path/to/datasets/hcpya-u100/derivatives/sc-initsurf
+    OASIS1: /path/to/datasets/oasis-1/derivatives/sc-initsurf
+
+  log_dir: /path/to/simcortex-runs/initsurf/exp01_hcpya+oasis1/logs_generate
+
+params:
+  overwrite: false
+  validate_affine: true
+  affine_atol: 1.0e-4
+
+  gap_size: 1
+  sdf_sigma: 0.5
+  topo_threshold: 16.0
+  n_smooth: 1
+
+  wm_start_level: -0.2
+  wm_step: -0.08
+  wm_min_level: -3.0
+  wm_inset: 1.0
+
+  pial_min_level: 1.8
+  pial_max_level: 2.7
+  pial_grid_step: 0.1
+  pial_absolute_floor: 0.1
+
+hydra:
+  run:
+    dir: ${outputs.log_dir}
+  output_subdir: null
+  job:
+    chdir: false

zenodo-v2/configs/seg/eval.yaml

@@ -0,0 +1,48 @@
+dataset:
+  # Single-dataset mode:
+  #   Set dataset.path and outputs.pred_root.
+  # Multi-dataset mode:
+  #   Keep dataset.path: null and use dataset.roots + outputs.pred_roots.
+  path: null
+  name: null
+  split_file: /path/to/datasets/splits/dataset_split.csv
+  split_name: test
+  session_label: "01"
+  space: MNI152
+
+  roots:
+    HCP_YA: /path/to/datasets/hcpya-u100/derivatives/sc-preproc
+    OASIS1: /path/to/datasets/oasis-1/derivatives/sc-preproc
+
+evaluation:
+  num_classes: 9
+  exclude_background: true
+  eps: 1.0e-6
+  compute_nsd: true
+  nsd_tolerance_vox: 1.0
+  nsd_include_background: false
+  spacing: [1.0, 1.0, 1.0]
+
+outputs:
+  # Single-dataset prediction root:
+  pred_root: null
+
+  # Multi-dataset prediction roots produced by seg/inference.py.
+  pred_roots:
+    HCP_YA: /path/to/datasets/hcpya-u100/derivatives/sc-seg
+    OASIS1: /path/to/datasets/oasis-1/derivatives/sc-seg
+
+  eval_dir: /path/to/simcortex-runs/seg/exp01_hcpya+oasis1/evals
+  log_dir: ${outputs.eval_dir}/logs
+  eval_csv: ${outputs.eval_dir}/seg_eval_test.csv
+  eval_xlsx: ${outputs.eval_dir}/seg_eval_test.xlsx
+  failed_csv: ${outputs.eval_dir}/seg_eval_test_failed.csv
+  summary_csv: ${outputs.eval_dir}/seg_eval_test_summary_by_dataset.csv
+  summary_json: ${outputs.eval_dir}/seg_eval_test_summary.json
+
+hydra:
+  run:
+    dir: ${outputs.log_dir}
+  output_subdir: null
+  job:
+    chdir: false

zenodo-v2/configs/seg/inference.yaml

@@ -0,0 +1,59 @@
+# SimCortex segmentation inference config
+
+dataset:
+  # Single-dataset mode:
+  #   set path to one preprocessed derivative root and keep roots null/empty.
+  # Multi-dataset mode:
+  #   keep path null and define roots below.
+  path: null
+
+  split_file: /path/to/datasets/splits/dataset_split.csv
+
+  # Use "all" to create inputs for downstream InitSurf and deformation stages.
+  # Use "test" only for a test-only inference run.
+  split_name: all
+
+  session_label: "01"
+  space: "MNI152"
+  pad_mult: 16
+
+  roots:
+    HCP_YA: /path/to/datasets/hcpya-u100/derivatives/sc-preproc
+    OASIS1: /path/to/datasets/oasis-1/derivatives/sc-preproc
+
+model:
+  in_channels: 1
+  out_channels: 9
+  features: [16, 32, 64, 128, 128]
+  norm: instance
+  dropout: 0.10
+
+  ckpt_path: /path/to/seg_best_dice.pt
+
+trainer:
+  device: cuda:0
+  batch_size: 1
+  num_workers: 2
+  amp: true
+
+outputs:
+  # Single-dataset mode:
+  out_root: null
+
+  # Multi-dataset mode:
+  out_roots:
+    HCP_YA: /path/to/datasets/hcpya-u100/derivatives/sc-seg
+    OASIS1: /path/to/datasets/oasis-1/derivatives/sc-seg
+
+  log_dir: /path/to/simcortex-runs/seg/logs_infer
+
+  overwrite: false
+  overwrite_dataset_description: false
+  tensorboard: true
+
+hydra:
+  run:
+    dir: ${outputs.log_dir}
+  output_subdir: null
+  job:
+    chdir: false

zenodo-v2/configs/seg/train.yaml

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+# SimCortex segmentation training config
+
+dataset:
+  # Single-dataset mode:
+  #   set path to one derivative root and keep roots as null/empty.
+  # Multi-dataset mode:
+  #   keep path null and define roots below.
+  path: null
+
+  # Combined split CSV. In multi-dataset mode it must contain:
+  #   subject, split, dataset
+  split_file: /path/to/datasets/splits/dataset_split.csv
+
+  roots:
+    HCP_YA: /path/to/datasets/hcpya-u100/derivatives/sc-preproc
+    OASIS1: /path/to/datasets/oasis-1/derivatives/sc-preproc
+
+  train_split: train
+  val_split: val
+  session_label: "01"
+  space: "MNI152"
+
+  pad_mult: 16
+
+  augment: true
+
+model:
+  in_channels: 1
+  out_channels: 9
+
+  features: [16, 32, 64, 128, 128]
+  norm: instance   
+  dropout: 0.10    
+
+trainer:
+  batch_size: 2
+  num_workers: 4
+
+  device: cuda:0
+  use_ddp: true   
+  data_parallel: false
+
+  seed: 12345
+  deterministic: false
+
+  num_epochs: 1000
+  validation_interval: 5
+
+  optimizer: adamw
+  learning_rate: 1.0e-4
+  weight_decay: 1.0e-5
+
+  dice_weight: 1.0
+  dice_exclude_bg: true
+  dice_ignore_absent_target_classes: true
+  ce_class_weights: null
+
+  amp: true
+
+  grad_clip_norm: 1.0
+
+  scheduler:
+    name: cosine
+    eta_min: 1.0e-6
+
+  save_interval: 25
+  keep_last_n_checkpoints: 3
+
+  early_stop_patience: 30
+
+  resume_from: null
+
+outputs:
+  root: /path/to/simcortex-runs/seg/exp01_hcpya+oasis1
+  log_dir:  ${outputs.root}/logs_train
+  ckpt_dir: ${outputs.root}/checkpoints
+
+
+hydra:
+  run:
+    dir: ${outputs.log_dir}
+  output_subdir: null
+  job:
+    chdir: false

zenodo-v2/deform/deform_best_model.pth

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+size 24220666

zenodo-v2/deform/deform_best_rmse.pth

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zenodo-v2/provenance.json

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+{
+  "release": "SimCortex v2 pretrained models",
+  "primary_deformation_checkpoint": {
+    "file": "deform/deform_best_rmse.pth",
+    "role": "recommended checkpoint used for the final paper evaluation",
+    "sha256": "3fb84c917953e479e72d59291837bd6b08f40fb197534046b95dc5a452e86b95"
+  },
+  "secondary_deformation_checkpoint": {
+    "file": "deform/deform_best_model.pth",
+    "role": "alternative checkpoint retained for reproducibility and comparison",
+    "sha256": "d30d3218069a6eb395dacd3ff0dd085a93f6f0102616eed809b90c362b885b40"
+  },
+  "segmentation_checkpoint": {
+    "file": "seg/seg_best_dice.pt",
+    "sha256": "2cea6dc1606958dbdb2aea50748b73ff73e604b0c367b3b1588cef7a112c8e06"
+  },
+  "training_split": {
+    "file": "splits/dataset_split.csv",
+    "subjects": 515,
+    "train": 361,
+    "validation": 77,
+    "test": 77,
+    "sha256": "68f42ef3ed09373685de5d1dd144c7d3d72b7f8083850057dcccd5780756188d"
+  },
+  "evaluation_cohort": {
+    "file": "splits/evaluation_sample40.csv",
+    "cases": 560,
+    "datasets": 14,
+    "cases_per_dataset": 40,
+    "sha256": "2c41b21afea327756c8d7fccc30bd03e461670d59dc00f941e8cba06fcf59842"
+  }
+}

zenodo-v2/seg/seg_best_dice.pt

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zenodo-v2/splits/evaluation_sample40.csv

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