metadata
license: mit
license: mit
π Model Card for Hugging Face (ProViCNet Weights)
ProViCNet: Prostate-Specific Foundation Models with Patch-Level Contrast for Cancer Detection
π 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.
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.
π For usage examples and detailed documentation, visit:
π ProViCNet GitHub Repository
π Reference Paper:
π ProViCNet: Organ-Specific Foundation Model for Prostate Cancer Detection