SelfRDB Checkpoints

📝 Summary

This release includes pretrained models for medical image translation tasks across three datasets: IXI, BRATS, and CT. Each model has been trained using PyTorch Lightning to perform specific translation tasks.

🦁 Model Zoo

PSNR (dB) and SSIM (%) are listed as mean ± std across the test set.

Dataset	Task	PSNR	SSIM	Checkpoint
IXI	T2→T1	31.63 ± 1.53	95.64 ± 1.12	Link
IXI	T1→T2	31.28 ± 1.56	95.03 ± 1.27	Link
IXI	PD→T1	31.23 ± 1.22	95.64 ± 0.99	Link
IXI	T1→PD	32.17 ± 1.57	95.15 ± 0.99	Link
BRATS	T2→T1	28.85 ± 1.48	93.70 ± 1.87	Link
BRATS	T1→T2	27.58 ± 1.88	92.99 ± 2.44	Link
BRATS	FLAIR→T2	26.85 ± 1.75	91.66 ± 2.72	Link
BRATS	T2→FLAIR	27.98 ± 1.80	90.01 ± 2.70	Link
CT	T2→CT	29.18 ± 2.18	93.28 ± 1.99	Link
CT	T1→CT	27.55 ± 3.32	92.29 ± 6.32	Link

📋 Usage Instructions

To use these pretrained models, follow the instructions provided in the README.md file of the repository

🗒️ Notes

These models are designed for specific medical image translation tasks and may require dataset-specific preprocessing.