| { |
| "_ilex": { |
| "architecture": "ilex.models.synthstrip.model.SynthStrip", |
| "constructor_kwargs": { |
| "feat_mult": 2, |
| "inshape": null, |
| "max_features": 64, |
| "max_pool": 2, |
| "nb_conv_per_level": 2, |
| "nb_features": 16, |
| "nb_levels": 7, |
| "return_mask": false |
| }, |
| "format": "ilex", |
| "framework_version": { |
| "equinox": "0.13.8", |
| "ilex": "0.0.0.dev0", |
| "jax": "0.10.0", |
| "jaxlib": "0.10.0", |
| "numpy": "2.4.4", |
| "safetensors": "0.7.0" |
| }, |
| "has_state": false, |
| "origin": "ilex-native" |
| }, |
| "authors": "Hoopes A., Mora J. S., Dalca A. V., Fischl B., Hoffmann M.", |
| "copyright": "Network architecture and training code: copyright (c) 2022 The General Hospital Corporation, distributed as part of FreeSurfer (GPL-2.0). Pretrained weights: dual-licensed by upstream as MIT or CC-BY-4.0 (see https://surfer.nmr.mgh.harvard.edu/docs/synthstrip/). JAX / Equinox port: copyright (c) the ilex authors, released under the Apache-2.0 / GPL-3.0 dual license used by ilex itself.", |
| "data_type": "nibabel", |
| "description": "SynthStrip skull-stripping network ported to JAX / Equinox from the FreeSurfer mri_synthstrip reference implementation. The network is trained with synthesis-based domain randomisation and is contrast-agnostic across modalities (T1w, T2w, FLAIR, DWI, etc.). It outputs a signed distance transform (SDT) of the brain surface; downstream tooling thresholds the SDT to obtain a binary brain mask.", |
| "equinox_version": "0.13.8", |
| "ilex_version": "0.0.0.dev0", |
| "image_classes": "Single-channel 3D structural MRI volume, contrast-agnostic. Inputs at 1 mm isotropic voxel size and conformed to LIA orientation are recommended for parity with the published checkpoint behaviour.", |
| "intended_use": "Research only. Skull stripping of 3D structural MRI volumes that have been conformed to 1 mm isotropic voxels, intensity-normalised (subtract minimum, divide by 99th percentile, clip to [0, 1]), and padded to a multiple of 64 along each spatial axis -- see the FreeSurfer mri_synthstrip preprocessing pipeline.", |
| "jax_version": "0.10.0", |
| "network_data_format": { |
| "inputs": {}, |
| "outputs": {} |
| }, |
| "numpy_version": "2.4.4", |
| "pred_classes": "Single-channel signed distance transform of the brain surface (positive outside, negative inside). Threshold at 1 mm to obtain the binary brain mask used by mri_synthstrip's CLI.", |
| "references": [ |
| "Hoopes A., Mora J. S., Dalca A. V., Fischl B., Hoffmann M. (2022). SynthStrip: Skull-Stripping for Any Brain Image. NeuroImage, 260:119474. doi:10.1016/j.neuroimage.2022.119474", |
| "Kelley W. et al. (2024). Boosting Skull-Stripping Performance for Pediatric Brain Images. IEEE International Symposium on Biomedical Imaging (ISBI).", |
| "Hoffmann M. (2025). Domain-Randomized Deep Learning for Neuroimage Analysis. IEEE Signal Processing Magazine." |
| ], |
| "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20240725.json", |
| "task": "Skull stripping (brain extraction) of structural MRI volumes", |
| "version": "0.1.0" |
| } |
