Welcome to the QMENTA SDK documentation!

Introduction

The QMENTA Platform provides a unified solution for data management, processing and visualisation. The analyses (medical imaging processing tools) are executed on the hybrid cloud infrastructure as Docker containers and treated as black boxes that communicate with the platform using our SDK.

A simple Python program connects the QMENTA Platform with any third-party program. This typically involves fetching the input data, starting the binaries or scripts and uploading the result files in a compartmentalized, traceable and secure computing environment.

Any data uploaded to the platform can be used for analysis with a simple step, and the resulting files can be managed and visualized within the same platform website.

In addition, tools can also be seamlessly customized to include external parameters using GUI elements that provide an easy way for users to choose between different options and tune the execution flow of the analyses.

Tool Maker guide

We invite you to get started with the QMENTA SDK by reading this guide introducing the QMENTA Tool Maker to integrate your first algorithm in the QMENTA platform.

• Install the QMENTA SDK
  • Install Python Package
  • Extend Docker Image
• Working with Docker images
  • Committing containers
  • Using a Dockerfile
• Tool development using the Tool Maker
  • Creating a new tool
  • Local Testing Guidelines
  • Test in docker container
  • Integrate your tool in the QMENTA Platform
  • Integrate your workflow in the QMENTA Platform

Tool tutorial

If you are looking for more in-depth information about specific stages in the tool development process with the QMENTA SDK, we recommend you to read the following documents.

• Tool tutorial
  • Before you begin
  • Write the main Python program
  • Test the tool locally
  • Package your tool in a Docker image
  • Add the tool to the platform
  • Run your tool in the QMENTA platform

The following pages contain information that, while still functional, is considered outdated. These sections provide guidance on integrating a tool into the QMENTA Platform; however, they require manual creation of all necessary files. It is now recommended to utilize the QMENTA Tool Maker, which automates this process. Nevertheless, for those interested in exploring the underlying details, these pages remain available for reference.

• Legacy topics
  • Tool development with the SDK
  • Testing tools locally
  • Adding a tool to the platform
  • Advanced topics

Examples

You can also find concrete examples of how the QMENTA SDK can be used in a variety of tool development scenarios.

Note

This examples are not using QMENTA Tool Maker. You can find one example here: <a href=”https://github.com/QMENTA/qmenta-sdk-tool-maker-example” target=”_blank”>QMENTA SDK Tool maker Example</a>

• Examples
  • Simple mrinfo tool
  • MATLAB-based tool
  • IronTract Challenge dMRI tractography reconstruction w/ DIPY, by Gabriel Girard

API Reference

In the API reference you can find detailed documentation about the attributes and methods of the two main classes available in the SDK: qmenta.sdk.context.AnalysisContext and qmenta.sdk.context.File.

• API Reference
  • Tool Maker
  • AnalysisContext
  • File

Community

Lastly, we invite you to join the conversation and get support from fellow developers and QMENTA representatives in the Brain Innovation Hub.

• Join the Community