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Lexer1
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VSSR

PyTorch
mri
medical-imaging
image-reconstruction
accelerated-mri
monai
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VSSR
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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 — 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 — one per anatomical plane (sagittal, axial, coronal) — 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/
├── vssr_stage1_sagittal.pth      ← RDUNet SAC cascade, Stage 1
├── vssr_stage2_axial.pth         ← RDUNet SAC cascade, Stage 2
├── vssr_stage3_coronal.pth       ← RDUNet SAC cascade, Stage 3 (final output)
├── baselines/
│   ├── sunet_sagittal_8x.pth     ← Single-view SUNet baseline
│   ├── sunet_axial_8x.pth
│   └── sunet_coronal_8x.pth
├── cascades_8x/
│   └── SAC_final.pth             ← Best cascade 8× (PSNR 31.28 dB on IXI)
└── cascades_4x/
    └── SAC_final.pth             ← Best cascade 4×
```

### 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** — publicly available at [brain-development.org/ixi-dataset](https://brain-development.org/ixi-dataset/), 8× retrospective undersampling
- **Sheba Medical Center** — 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 — see the [GitHub repository](https://github.com/MR-Nazarov/VSSR).