Introduction

This guide is intended to provide a quick and easy way to get started with developments on the Kaapana platform.

The guide currently consists of three parts. This part gives a brief overview over the technologies and needed preparations for the rest of the guide. The part Developing Workflows focuses on the integration of custom processing workflows into the platform. It will be explained how to formulate workflows in Airflow-DAGs and further how to integrate workflows as extensions into the Kaapana technology stack. The last section Developing Applications gives step by step instructions how to deploy a general–purpose web application within Kaapana as an example how new components can be added to the platform.

List of the technologies

These tutorials/technologies are good references, when starting with the Kaapana deployment:

  • Docker: Necessary when you want to build containers on your local machine

  • Airflow: Our pipeline tool for processing algorithms

  • Kubernetes: (Advanced) On your local machine - necessary when you want to talk to the Kubernetes cluster from your local machine

  • Helm: (super advanced) - our package manager for Kubernetes. Necessary when you want to build helm packages on your local machine

All of the examples below are taken from the templates_and_examples folder of our Github repository!

Requirements

  • Running version of the Kaapana platform and access to a terminal where the platform is running

  • Installation of Docker on your local machine

  • optional: Installation of DCMTK to send images to the platform, but you can also use the Data Upload tool of the Kaapana platform

Upload images to the platform

There are two options how to upload images to the platform

  • Zip the DICOM or Nifti images which you want to upload to the platform in a .zip-folder and drag&drop the zipped folder in the Data Upload tool

  • Send images with dcmtk e.g.:

dcmsend -v <ip-address-of-server> <dicom port, default:11112> --scan-directories --call <dataset-name> --scan-pattern '*.dcm' --recurse <data-dir-of-DICOM-images>

To check whether the data was sucessfully uploaded to the platform, navigate to Workflows -> Datasets and you will find your data!

Note

In order to get a general idea about how to use the platform and to get an idea about its individual parts checkout the User Guide.