The facility provides access to proprietary analysis software, open source software and tools developed in house. We also provide access to deep-learning solutions including the training on your own data on our machines.

proprietary     open-source     deep-learning     tools


Automatic detection and segmentation of cells and nuclei using star-convex polygons.

Use dl4mic to train and apply StarDist.

Symphotime (PicoQuant)

Fluorescence Lifetime Imaging and Correlation Software

  • Powerful 64bit TTTR data acquisition and analysis software
  • Point, 2D, and 3D data acquisition with online preview of FLIM, FCS, time-traces, or TCSPC histograms
  • FCS, FCCS, FLCS, PIE-FCS, coincidence correlation, total correlation
  • Fluorescence time trace analysis, single molecule burst analysis
  • Anisotropy
  • TCSPC lifetime fitting with advanced error treatment
  • User programming script language "STUPSLANG"

See symphotime-64-fluorescence-lifetime-imaging-and-correlation-software



UNet is a deep-learning method for pixel classification. It can be trained to segment different kinds of objects in images. The first half of the U-Net architecture is a downsampling convolutional neural network which acts as a feature extractor from input images. The other half upsamples these results and restores an image by combining results from downsampling with the upsampled images. Use dl4mic to train and apply the UNet.

Volocity (Quorum)

Moving seamlessly among restoration, visualization and quantitation, Volocity software is designed for true 3D analysis of fluorescence images. View your cells from every angle. Measure shapes, volumes and distances. Relate cellular structure to function with exceptional precision and speed. Compare samples and identify trends. Produce publication-ready tables and charts. Take your image analysis to a new dimension with true 3D image analysis.