Kaapana

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".

Blockchain & Cloud ComputingPythonAGPL-3.0

Abstract

Kaapana is an open-source Blockchain & Cloud Computing project. 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". 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. It is built using Python, Kubernetes. The complete source code is publicly available on GitHub under the GNU Affero General Public License v3.0, making it a useful reference for students building a Blockchain & Cloud Computing mini project or final-year project.

1. Introduction

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".

Following this federated concept, the goal of Kaapana is to provide a framework and a set of tools for sharing data processing algorithms, for standardized workflow design and execution as well as for performing distributed method development. This will facilitate data analysis in a compliant way enabling researchers and clinicians to perform large-scale multi-center studies.

By adhering to established standards and by adopting widely used open technologies for private cloud development and containerized data processing, Kaapana integrates seamlessly with the existing clinical IT infrastructure, such as the Picture Archiving and Communication System (PACS), and ensures modularity and easy extensibility.

2. Objective

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".

This project demonstrates how Python, Kubernetes can be applied to a real-world Blockchain & Cloud Computing problem.

4. Technology Stack

PythonKubernetes

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

  • Python 3.8 or later
  • pip / virtualenv for dependencies
  • VS Code, PyCharm or Jupyter Notebook
  • Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/kaapana/kaapana.git
cd kaapana

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

  • Add a CI/CD pipeline with GitHub Actions
  • Deploy to a public test network or cloud free tier
  • Add monitoring and cost alerts

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

  1. Why does this problem need a blockchain or cloud-native design?
  2. Explain the smart contract / infrastructure components and how they interact.
  3. How are gas costs or cloud costs kept under control?
  4. How is the system secured (keys, IAM, access control)?
  5. How would the solution scale to many more users?

9. Source Code & License

This project is developed by kaapana and published on GitHub under the GNU Affero General Public License v3.0. Please follow the license terms and credit the original author when you use or modify this code.

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