Microscopy Imaging Center



(National institutes of Health)

OpenSource software (help can be provided)

  • Visualization of Data (8, 16, 32 bit data/ TIFF, PNG, GIF, DICOM, LSM, FITS,MRC, …)
  • Cross platform (compatible with Windows (XP, Vista & 7), Mac Os X, Linux)
  • Extendible (e.g. stereology, Cell counter, deconvolution, FFT, hyperstacks, …)

Contact:  Dr. Guillaume Witz


Python is currently the most popular programming language for image processing research software development. Via various packages such as numpy, scikit-image, pytorch it offers a very large range of functionalities for almost any image processing task. In particular, most cutting-edge development in Machine Learning and Deep Learning is done in Python. The language’s simplicity makes it a popular choice among beginners allowing them to quickly access powerful features and to write their own scripts and software. The Jupyter software provides an interactive interface for Python (and other languages like R) which makes it an ideal tool when developing step by step an image analysis pipeline. One of the main advantages of Jupyter is the possibility to use it in combination with any computing infrastructure, and therefore offering a seamless access to high-performance computing. Finally, napari, a Python package, offers a powerful multi-dimensional visualiser for the Python world. It can easily be extended via a plugin system similar to Fiji and is ideally suited to people who prefer to use a graphical user interface. It is important to note that the Python eco-system makes it very easy to share entirely reproducible workflows via services such as Google Colab or Binder.

We offer regular courses for scientific computing with Python, including introductions for beginners, specific courses dedicated to essential libraries like numpy and pandas, as well as an image processing focused course, and an introduction to deep learning for imaging. We offer complete support for the development of new custom software in Python, including algorithm implementations, user interface development etc.

Contact:  Dr. Guillaume Witz


(Broad Institute)

CellProfiler is a Python-based software for bioimage processing. It essentially offers a graphical interface to create standard image processing pipelines that would otherwise have to be written in scripts. It guides the user through all steps of a pipeline (image import, segmentation, analysis) and offers a wide-range of “modules” to achieve all these tasks. In particular it also offers modules dedicated to specific domains (e..g the Wormtoolbox to analyze C.elegans data). CellProfiler is particularly well-suited for the analysis of High-throughput experiments.


We offer regular training for CellProfiler (~ once per year) where people can learn how to create their own pipeline. We also offer support to users for the creation of new pipelines and the development of custom modules that can be integrated into CellProfiler.

Contact: Dr. Guillaume Witz



Ilastik is a graphical interface software allowing for segmentation of a large variety of image types (EM, FM, volumes etc) using both Machine Learning and Deep Learning methods. It makes it particularly easy to annotate images to “teach” the algorithm to recognize specific structures. Trained algorithms can then be re-used on images of the same type therefore allowing to automate the often very tedious annotation task. Additionally, Ilastik also offers a tracking feature that uses information about segmented objects shapes to link them across time frames. Ilastik can be called programmatically and therefore included in larger analysis pipelines.

We offer regular trainings on Ilastik (~ once per year) generally with one of the software developers. We offer support of the usage of Ilastik and its deployment on high performance computing resources.

Contact: Dr. Guillaume Witz


(Bitplane AG, Switzerland)

  • For visualisation of 3D confocal data (or tiff series)
  • Visualisation of time series (4D)
  • Surpass modul: for volume and surface rendering, object quantification, object measurement
  • Colocalisation modul

Contact:  Dr. Guillaume WitzDr. Fabian Blank (for DBMR members)

Huygens essentials

(Scientific Volume Imaging, Netherlands)

  • Deconvolution software for microscopic images (confocal, widefield)
  • PSF distiller software included

Contact:  Dr. Yury Belyaev

Huygens Remote Manager (HRM)

(Scientific Volume Imaging, Netherlands)

  • Web-based batch deconvolution for all types of microscopic images
  • Server with GPU acceleration
  • Access online (university network only!)

Contact:  Dr. Yury Belyaev


(Boulder Laboratory for 3-D Electron Microscopy of Cells)

  • image processing, modeling and display of TEM serial sections and optical sections
  • tomographic reconstruction and 3D reconstruction

Contact:  Dr. Dimitri Vanhecke


(S.Tschanz, Anatomy UNIBE, Switzerland)

  • Stereology tool

Contact:  PD Dr. Stefan Tschanz

UCSF Chimera


  • Protein Structure visualization
  • 3D map visualization and processing

Contact:  Prof. Dr. Benoît Zuber