The Quantitative Imaging Platform

Welcome to the Qim Platform, developed by the QIM center and hosted at the DTU Computing Center (DCC).

The platform is designed to streamline the quantitative analysis of large-scale 3D images by providing easy-to-use interfaces and access to a High-Performance Computing Cluster. It offers both local tools, which run on your browser using your computer’s resources, and remote tools that leverage the cluster’s computational power.

Currently in development, the platform will expand with additional features and tools over time. If you encounter any problems or have requests, do not hesitate to contact us.

Partners

Support

The development of the QIM Platform is supported by the Infrastructure for Quantitative AI-based Tomography QUAITOM which is supported by a Novo Nordisk Foundation Data Science Programme grant (Grant number NNF21OC0069766).

Platform resources

Here you can find a description of the resources available in the Qim platform, which can be accessed from the top menu.

Libraries

The platform relies on other libraries for its functionalities.

Documentation

Here it is possible to find the documentation for the related libraries that deal with volumetric imaging. If you want to have the documentation of your library linked here or hosted on the Qim platform, do not hesitate to contact us.

• qim3d Library designed for Quantitative Imaging in 3D using Python. It offers a range of features, including data loading and manipulation, image processing and filtering, data visualization, and analysis of imaging results.

Data

Handling data, particularly with volumetric imaging where datasets can rapidly grow in size, can be challenging. The Qim platform is designed to assist by offering specialized tools to manage and analyze your data effectively.

File explorer

We provide a web sftp client using Filestash, which is suitable for light interaction with the file servers. A tutorial on how to use it can be found here.

• Home Access your home directory where you can manage your files.
• Gbar Direct link to the root of the Gbar file server.
• Projects Directories of the Qim and 3d-imaging related projects.
• Courses Find and manage course-related files and resources.
• Jupyter Notebooks Collection of Jupyter notebooks related to volumetric imaging.

Data exploration

• Public data Collection of publicly available files. Right-click a file or folder for more options, like visualization.

Data management

• Data upload We're currently working on a web system to get data uploaded to DTU servers. Meanwhile, check our Globus transfer tutorial.

Tools

To facilitate your work with volumetric imaging data, the Qim platform provides a range of tools.

Remote tools

The remote tools will use resources from the DTU Computing Center (DCC) so being logged in is necessary. They will submit jobs to the High Performance Computing (HPC) cluster, and provide you with interfaces to interact with the result.

• Tool launcher Launch graphical user interfaces (GUIs) from the qim3d library.
• Jupyter launcher Start a Jupyter Notebook server.

Local tools

The local tools do not interact with DCC, they run directly in your browser, thus using your own computer for processing. Thus, they are available without the need for login.

• JupyterLite A lightweight version of Jupyter for quick, local notebook execution.
• ImageJ An open-source image processing tool for analyzing and visualizing images.
• Pyodide A Python interpreter for running Python code directly in the browser.
• VolView A tool for visualizing and analyzing volumetric data.
• itk-vtk-viewer A viewer for interactive visualization of ITK and VTK datasets.