Kaapana
An open-source toolkit for federated learning and AI workflow management in medical imaging analysis.
What is Kaapana?
Kaapana is an open-source toolkit for platform provisioning in medical data analysis, specifically designed for AI-based workflows and federated learning in radiological and radiotherapeutic imaging. It provides a framework for sharing data processing algorithms, standardized workflow design, and distributed method development while keeping data under the authority of individual institutions. The toolkit integrates with existing clinical IT infrastructure like PACS systems to facilitate compliant multi-center studies.
Medical researchers, clinicians, and data scientists working on multi-center medical imaging studies, particularly in radiology and radiotherapy, who need federated learning capabilities and AI workflow management.
Developers choose Kaapana for its federated approach that overcomes legal and technical hurdles in multi-center medical data analysis, its seamless integration with clinical IT infrastructure, and its modular, extensible design using open technologies like Kubernetes and Airflow.
Overview
Kaapana is an open source toolkit for state of the art platform provisioning in the field of medical data analysis. The applications comprise AI-based workflows and federated learning scenarios with a focus on radiological and radiotherapeutic imaging. The name Kaapana comes from the Hawaiian word kaʻāpana, meaning "distributor" or "part".
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