| --- |
| license: mit |
| library_name: pytorch |
| tags: |
| - medical |
| - segmentation |
| - stroke |
| - neurology |
| - mri |
| pipeline_tag: image-segmentation |
| --- |
| |
| # qSynth |
|
|
| Synthseg-style model trained on qMRI-constrained synthetic data derived from OASIS3 tissue maps and ATLAS binary lesion masks. |
|
|
| ## Model Details |
|
|
| - **Name**: qSynth |
| - **Classes**: 0 (Background), 1 (Gray Matter), 2 (White Matter), 3 (Gray/White Matter Partial Volume), 4 (Cerebro-Spinal Fluid), 5 (Stroke) |
| - **Patch Size**: 192³ |
| - **Voxel Spacing**: 1mm³ |
| - **Input Channels**: 1 |
|
|
| ## Usage |
|
|
| ### Loading from Hugging Face Hub |
|
|
| ```python |
| import torch |
| from synthstroke_model import SynthStrokeModel |
| |
| # Load the model from Hugging Face Hub |
| model = SynthStrokeModel.from_pretrained("liamchalcroft/synthstroke-qsynth") |
| |
| # Prepare your input (example shape: batch_size=1, channels=1, H, W, D) |
| input_tensor = torch.randn(1, 1, 192, 192, 192) |
| |
| # Get predictions (with optional TTA for improved accuracy) |
| predictions = model.predict_segmentation(input_tensor, use_tta=True) |
| |
| # Get tissue probability maps |
| background = predictions[:, 0] # Background |
| gray_matter = predictions[:, 1] # Gray Matter |
| white_matter = predictions[:, 2] # White Matter |
| partial_volume = predictions[:, 3] # Gray/White Matter PV |
| csf = predictions[:, 4] # Cerebro-Spinal Fluid |
| stroke = predictions[:, 5] # Stroke lesion |
| |
| # Alternative: Get logits without TTA |
| logits = model.predict_segmentation(input_tensor, apply_softmax=False) |
| ``` |
|
|
| ## Citation |
|
|
| [arXiv](https://www.arxiv.org/abs/2412.03318) |
|
|
| ```bibtex |
| @misc{chalcroft2025domainagnosticstrokelesionsegmentation, |
| title={Domain-Agnostic Stroke Lesion Segmentation Using Physics-Constrained Synthetic Data}, |
| author={Liam Chalcroft and Jenny Crinion and Cathy J. Price and John Ashburner}, |
| year={2025}, |
| eprint={2412.03318}, |
| archivePrefix={arXiv}, |
| primaryClass={eess.IV}, |
| url={https://arxiv.org/abs/2412.03318}, |
| } |
| ``` |
|
|
| ## License |
|
|
| MIT License - see the [LICENSE](https://github.com/liamchalcroft/synthstroke/blob/main/LICENSE) file for details. |
|
|
