VSSR / README.md
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Add 4x SAC cascade to model card
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---
license: cc-by-sa-4.0
tags:
- mri
- medical-imaging
- image-reconstruction
- accelerated-mri
- pytorch
- monai
library_name: pytorch
---
# VSSR: View-Specialized Sequential Refinement for Accelerated MRI
**Post-Reconstruction Volumetric Refinement for Accelerated MRI via Cross-Plane Consistency**
*IEEE Engineering in Medicine and Biology Conference (EMBC) 2026 β€” Paper ID: 4868*
Alexander Nazarov, Nahum Kiryati, Dani Roizen, Gahl Greenberg, Arnaldo Mayer
*Tel-Aviv University & Sheba Medical Center*
---
## Overview
VSSR is a post-reconstruction refinement framework for accelerated MRI. Three view-specialized expert networks refine the volume sequentially β€” one per anatomical plane (sagittal, axial, coronal) β€” each correcting the residual artifacts left by the previous stage.
**Code & instructions:** [github.com/MR-Nazarov/VSSR](https://github.com/MR-Nazarov/VSSR)
---
## Model Weights
```
Lexer1/VSSR/
β”œβ”€β”€ vssr_stage1_sagittal.pth ← RDUNet SAC cascade, Stage 1
β”œβ”€β”€ vssr_stage2_axial.pth ← RDUNet SAC cascade, Stage 2
β”œβ”€β”€ vssr_stage3_coronal.pth ← RDUNet SAC cascade, Stage 3 (final output)
β”œβ”€β”€ baselines/
β”‚ β”œβ”€β”€ sunet_sagittal_8x.pth ← Single-view SUNet baseline
β”‚ β”œβ”€β”€ sunet_axial_8x.pth
β”‚ └── sunet_coronal_8x.pth
β”œβ”€β”€ cascades_8x/
β”‚ └── SAC_final.pth ← Best cascade 8Γ— (PSNR 31.28 dB on IXI)
└── cascades_4x/
└── SAC_final.pth ← Best cascade 4Γ—
```
### Download
```python
from huggingface_hub import hf_hub_download
path = hf_hub_download(repo_id="Lexer1/VSSR", filename="cascades_8x/SAC_final.pth")
```
Or download all weights at once:
```bash
hf download Lexer1/VSSR --local-dir ./models
```
---
## Training Data
- **IXI dataset** β€” publicly available at [brain-development.org/ixi-dataset](https://brain-development.org/ixi-dataset/), 8Γ— retrospective undersampling
- **Sheba Medical Center** β€” prospectively accelerated in-house dataset (not publicly available)
---
## Citation
```bibtex
@inproceedings{nazarov2026vssr,
title = {Post-Reconstruction Volumetric Refinement for Accelerated {MRI} via Cross-Plane Consistency},
author = {Nazarov, Alexander and Kiryati, Nahum and Roizen, Dani and Greenberg, Gahl and Mayer, Arnaldo},
booktitle = {2026 IEEE Engineering in Medicine and Biology Conference (EMBC)},
year = {2026},
note = {Paper ID: 4868}
}
```
---
## License
Model weights are licensed under [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/).
Code is licensed under MIT β€” see the [GitHub repository](https://github.com/MR-Nazarov/VSSR).