Center for Quantification of Imaging Data from MAX IV
At Qim we develop algorithms for quantitative image analysis in order to support the research carried out at large-scale imaging facilities.
Web platform
Online tools for visualization and analysis of imaging data and access to the HPC resources of DTU Compute
Python library
Development of qim3d, an open source library for quantitative image analysis
Method development
Developing new algorithms for quantitative imaging, with focus on 3D microscopy and tomography
Datasets
Volumetric data from imaging experiments, openly available for method development and benchmarking
Scanning support
High-resolution imaging services and support for experimental setup, sample preparation, and imaging strategies
Training
Workshops, courses, and tutorials to support researchers in quantitative imaging methods and tools
Key features of the Qim Center
We offer tools and resources to support imaging data analysis, method development, and reproducible research workflows.
![map[class:aspect-square object-cover object-center w-[75%] rounded-[32px] src:images/home/features/features-1.png]](/images/home/features/features-1.png)
Web interface
Access from anywhere
Web platform for imaging data
Our online platform allows visualization, analysis, and sharing of imaging datasets with integrated access to HPC resources at DTU Compute. Users can explore, annotate, and export volumetric data easily, while collaborating with colleagues in a fully secure environment. The platform supports multiple file formats and provides interactive visualization tools for 3D microscopy and tomography datasets.
![map[class:aspect-square object-cover object-center w-[75%] rounded-[32px] src:images/home/features/features-2.png]](/images/home/features/features-2.png)
Python tools
Open-source library
qim3d Python library
A library for quantitative 3D image analysis, supporting method development and reproducible workflows. It offers modules for segmentation, filtering, and feature extraction of volumetric datasets. Extensive documentation, examples, and tutorials make it easy to integrate into research pipelines and combine with other scientific Python packages for advanced data analysis.
![map[class:aspect-square object-cover object-center w-[75%] rounded-[32px] src:images/home/features/features-3.png]](/images/home/features/features-3.png)
Custom algorithms
Method development
Algorithm development tools
Develop new quantitative imaging algorithms with a focus on 3D microscopy, tomography, and volumetric data analysis. Our environment allows testing and benchmarking algorithms efficiently, including GPU acceleration and batch processing. Researchers can experiment with new approaches and validate results with standardized datasets, enabling reproducible and high-quality outcomes.
![map[class:aspect-square object-cover object-center w-[75%] rounded-[32px] src:images/home/features/server.png]](/images/home/features/server.png)
Data management
Open datasets
Datasets & benchmarking
Access volumetric imaging datasets for method testing, benchmarking, and reproducible research. The datasets include diverse imaging modalities and biological samples, all curated for quality and consistency. They can be freely downloaded, integrated into pipelines, or used for training machine learning models, providing a solid foundation for algorithm validation and comparative studies.
Data analysis
Visualization & insights
Data analysis & visualization
Tools for quantitative analysis and visual representation of imaging data to enable reproducible and interpretable results. Users can generate plots, 3D renderings, and statistical summaries, while combining multi-modal datasets. This makes it easier to communicate results, detect patterns, and integrate findings into publications and presentations, all within a single environment.
Training
Workshops & tutorials
Training & support
Workshops, tutorials, and support to help researchers get started with quantitative imaging and data analysis workflows. We provide hands-on exercises, code examples, and guidance on best practices for reproducible research. Participants gain practical skills for working with 3D microscopy and tomography datasets, integrating computational tools, and effectively analyzing complex volumetric data.
The Qim Center is a partnership of
![map[alt:DTU class:h-28 w-auto src:images/home/partners/DTU.png]](/images/home/partners/DTU.png)
![map[alt:KU class:h-28 w-auto src:images/home/partners/KU.png]](/images/home/partners/KU.png)
![map[alt:Lund class:h-28 w-auto src:images/home/partners/Lund.png]](/images/home/partners/Lund.png)
![map[alt:MaxIV class:h-28 w-auto src:images/home/partners/MaxIV.png]](/images/home/partners/MaxIV.png)