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| | license: bsd-2-clause
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| | ---
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| | # OCTCube Models Release
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| | This repository hosts the official release of **OCTCube-M: A 3D multimodal optical coherence tomography foundation model for retinal and systemic diseases with cross-cohort and cross-device validation**: [[Github repo](https://github.com/ZucksLiu/OCTCubeM)] | [[Arxiv](https://arxiv.org/abs/2408.11227)].
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| | We release **OCTCube**, **OCTCube-IR**, and a **Multi-task Classification Model** for 8 retinal diseases. These models are designed for **multi-modal OCT analysis** and support **image classification tasks** in ophthalmology.
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| | ## 🔹 Available Models
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| | | Model Name | Description |
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| | |------------|-------------|
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| | | OCTCube | A foundation model trained on OCT data for learning shared embeddings. |
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| | | OCTCube-IR | An infrared-enhanced version of OCTCube that integrates IR modality. |
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| | | Multi-task Classification Model | A model trained for multi-disease classification of 8 retinal diseases. |
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| | ## 📜 Model Details
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| | - **OCTCube**: Designed for learning joint representations of OCT images.
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| | - **OCTCube-IR**: Extends OCTCube by incorporating IR modality for improved alignment.
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| | - **Multi-task Classification Model**: A specialized classification model for **8 retinal diseases**, leveraging multi-task learning.
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| | ## 📂 Example Data
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| | - `oct_examples/`: Example OCT data volumes provided for trying our inference notebook! Includes:
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| | - `AMD.dcm`
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| | - `DR.dcm`
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| | - `POAG.dcm`
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| | - `DME.dcm`
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| | - `RNV.dcm`
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| | - `VD.dcm`
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| | - `ERM.dcm`
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| | - `CRAO/CRVO.dcm`
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| | ## 🔧 Usage
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| | To use the models in **PyTorch**, please check the [inference noteboook](https://github.com/ZucksLiu/OCTCubeM/blob/main/inference_OCTCube.ipynb).
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| | ## 📑 Citation
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| | If you use these models in your research, please cite:
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| | ```
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| | @article{liu2024octcube,
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| | title={OCTCube: a 3D foundation model for optical coherence tomography that improves cross-dataset, cross-disease, cross-device and cross-modality analysis},
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| | author={Liu, Zixuan and Xu, Hanwen and Woicik, Addie and Shapiro, Linda G and Blazes, Marian and Wu, Yue and Lee, Cecilia S and Lee, Aaron Y and Wang, Sheng},
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| | journal={arXiv preprint arXiv:2408.11227},
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| | year={2024}
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| | }
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| | ```
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| | ## 💬 Contact
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| | For any questions or feedback, feel free to open an issue or contact us directly (**zucksliu@cs.washington.edu**).
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| | ---
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| | 🚀 Stay tuned for updates and improvements!
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