Med-ImageNet is a transformative initiative to create an open-access, standardized medical imaging dataset for cancer research and clinical AI applications.
- build tools for data curation and standardization
- enable reliable AI models for tumor segmentation and treatment monitoring
- design a standard in radiological imaging data accessibility
- promote equitable access to healthcare data for AI research
- foster collaboration and innovation in the AI-driven cancer research community
- 🖼 Project Title: Med-ImageNet
- 🧬 Objective: Standardize and curate oncology imaging data to support AI-driven cancer research, focusing on auto-segmentation, treatment planning, and monitoring.
- 🌐 Significance: Tackles the lack of standardized healthcare imaging data, making data FAIR (Findable, Accessible, Interoperable, and Reusable) for machine learning applications.
- 💻 Innovations: Develops MedImage-Tools for data standardization, providing a comprehensive, open-source dataset for cancer imaging.
- 🌍 Equity and Inclusion: Prioritizes data inclusivity by representing diverse populations in cancer research.