daniel-scholz/mm-dinov2
Code for MM-DINOv2: Adapting Foundation Models for Multi-Modal Medical Image Analysis (MICCAI2025)
This project helps medical researchers and practitioners classify glioma subtypes from multi-modal medical images. By inputting various types of medical scan images, it provides a classification of the glioma subtype, which is crucial for diagnosis and treatment planning. This is intended for medical image analysis specialists, clinical researchers, and oncologists working with brain tumor imaging.
Use this if you are a medical researcher or clinician needing to classify glioma subtypes using multi-modal medical imaging data.
Not ideal if you are looking to analyze general medical images or different types of tumors beyond gliomas, or if you need to deploy this in a commercial setting due to its non-commercial license.
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19
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2
Language
Python
License
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Category
Last pushed
Oct 27, 2025
Commits (30d)
0
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