Kaapana is an open-source toolkit designed for state-of-the-art platform provisioning in medical data analysis. It focuses on AI-based workflows and federated learning, particularly in radiological and radiotherapeutic imaging. The toolkit addresses the challenges of obtaining large medical datasets for machine learning by allowing data to remain under institutional authority and processed on-site. Kaapana offers a framework for sharing data processing algorithms, standardized workflow design, and distributed method development, enabling researchers and clinicians to conduct large-scale multi-center studies. It integrates with existing clinical IT infrastructure and employs open technologies for private cloud and containerized data processing, ensuring modularity and easy extensibility. Key features include integration of the Medical Imaging Interaction Toolkit (MITK) for interactive medical image processing and nnU-Net for automated segmentation workflows.
• federated learning capabilities
• data processing algorithms sharing
• standardized workflow design and execution
• integration with existing clinical it like pacs
• modularity and extensibility
• mitk integration for medical image processing
• automated segmentation using nnu-net
Average Rating: 0.0
5 Stars:
0 Ratings
4 Stars:
0 Ratings
3 Stars:
0 Ratings
2 Stars:
0 Ratings
1 Star:
0 Ratings
No ratings available.
AI-enabled precision medicine platform for improving patient outcomes in healthcare.
View DetailsA federated AI framework that integrates decentralized data sources for AI development.
View Details