Add comprehensive model card

This PR adds a comprehensive model card for CoCoLIT, ensuring better discoverability and documentation on the Hugging Face Hub.

It includes:
- The `license` (`cc-by-nc-4.0`)
- The `pipeline_tag` (`image-to-image`)
- A link to the paper ([CoCoLIT: ControlNet-Conditioned Latent Image Translation for MRI to Amyloid PET Synthesis](https://huggingface.co/papers/2508.01292))
- A link to the GitHub repository
- Installation instructions
- Usage examples
- The academic citation

Please review and merge this PR if everything looks good.

README.md

@@ -0,0 +1,52 @@
+---
+license: cc-by-nc-4.0
+pipeline_tag: image-to-image
+---
+
+# CoCoLIT: ControlNet-Conditioned Latent Image Translation for MRI to Amyloid PET Synthesis
+
+This model, CoCoLIT, presents a diffusion-based latent generative framework for synthesizing amyloid PET scans from structural MRI. It addresses challenges in 3D neuroimaging data translation through a novel Weighted Image Space Loss (WISL), Latent Average Stabilization (LAS), and ControlNet-based conditioning for improved synthesis quality and inference consistency.
+
+**Paper**: [CoCoLIT: ControlNet-Conditioned Latent Image Translation for MRI to Amyloid PET Synthesis](https://huggingface.co/papers/2508.01292)
+**Code**: [https://github.com/brAIn-science/CoCoLIT](https://github.com/brAIn-science/CoCoLIT)
+
+<div align="center">
+  <img src="https://github.com/brAIn-science/CoCoLIT/raw/main/docs/assets/preview.gif"/>
+</div>
+
+## Installation
+
+This repository requires Python 3.10 and PyTorch 2.0 or later. To install the latest version, run:
+
+```bash
+pip install cocolit
+```
+
+## Usage
+
+After installing the package, you can convert a T1-weighted MRI to a Florbetapir SUVR map by running:
+
+```bash
+mri2pet --i /path/to/t1.nii.gz --o /path/to/output.nii.gz
+```
+
+To replicate the results presented in the paper, include the `--m 64` flag.
+
+<img width="100%" src="https://github.com/brAIn-science/CoCoLIT/raw/main/docs/assets/cocolit-cli.svg">
+
+## Disclaimer
+
+This software is not intended for clinical use. The code is not available for commercial applications. For commercial inquiries, please contact the corresponding authors.
+
+## Citing
+
+Arxiv Preprint:
+
+```bib
+@article{sargood2025cocolit,
+  title={CoCoLIT: ControlNet-Conditioned Latent Image Translation for MRI to Amyloid PET Synthesis},
+  author={Sargood, Alec and Puglisi, Lemuel and Cole, James H and Oxtoby, Neil P and Rav{\`\i}, Daniele and Alexander, Daniel C},
+  journal={arXiv preprint arXiv:2508.01292},
+  year={2025}
+}
+```