Welcome to the QMENTA SDK documentation!


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.

Getting started

We invite you to get started with the QMENTA SDK by following this step-by-step introductory tutorial to integrate your first algorithm in the QMENTA platform.


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.


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

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.


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