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| | license: mit |
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| | 📄 **Model Card for Hugging Face (ProViCNet Weights)** |
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| | ## **ProViCNet: Prostate-Specific Foundation Models with Patch-Level Contrast for Cancer Detection** |
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| | ### **📌 Overview** |
| | ProViCNet is an **organ-specific foundation model** designed for **prostate cancer detection** using **multi-modal medical imaging (mpMRI & TRUS)**. The model leverages **Vision Transformers (ViTs) with patch-level contrastive learning** to improve **cancer localization and classification**. |
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| | These pre-trained weights are provided for **research and clinical AI development** and can be used for **inference (feature extraction and cancer detection)** on prostate imaging datasets. |
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| | 📌 **For usage examples and detailed documentation, visit:** |
| | 🔗 **[ProViCNet GitHub Repository](https://github.com/pimed/ProViCNet/)** |
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| | 📄 **Reference Paper:** |
| | 🔗 **[ProViCNet: Organ-Specific Foundation Model for Prostate Cancer Detection](https://arxiv.org/abs/2502.00366)** |
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