Imaging of biological specimens plays an essential role in research across many scientific disciplines. It enables measurements and visualization of complex biological systems with a high spatial and temporal resolution, to generate and further test scientific hypotheses. 

The task of bioimage analysis is to “enable [computers] to automatically distinguish between relevant and irrelevant image information and to recognize and model spatial or temporal patterns of interest that could confirm or refute the hypotheses underlying the given experiment through quantitative analysis.” [4]

To fulfill this, image analysis services in academic facilities address all issues related to post-acquisition of biological imaging data from various imaging modalities. This covers image visualization, image processing and quantitative image analysis. 

Many image analysis software platforms and packages are available. An expert bioimage analyst will help choose and correctly utilize the right tool or combination of tools to build a workflow that will achieve the quantification goals. When needed, custom modules and tools will be developed. 

We support researchers with: 

  • Quantification projects and workflow development
  • Commercial software licenses 
  • Dedicated image analysis workstations
  • Courses and individual training for general image analysis concepts and for commercial and open source image analysis software. 

It is highly recommended to consult with a bioimage analyst at the beginning of a project to discuss experimental design related to image analysis.


Illustration of scinetific process

Selected References 

  1. "Hitchhiker’s Guide through the Bio-image Analysis Software Universe
  2. Image.sc 
  3. Image analysis training Resources by NEUBIAS Academy @ Home
  4. Meijering, Erik, et al. Imagining the future of bioimage analysis. Nat Biotechnol 2016.
  5. Introduction to Bioimage Analysis







Example Applications:

  • Pixel classification
  • Instance segmentation 
  • Nuclei and Cell Segmentation
  • 3D segmentation 
  • Tracking 
  • Colocalization 
  • Spatial analysis 
  • Fiber analysis 
  • Density analysis 
  • Morphological quantification
  • Background subtraction
  • Image enhancement 
  • Image reconstruction
  • Deconvolution
  • Image registration
  • Image alignment
  • Stitching



Commonly used open source software tools areFiji/ImageJ, Ilastik, QuPath, Napari, Icy, Cellprofiler, StarDist, Cellpose, Python image analysis and machine learning libraries 

Commercial software: Imaris, Arivis, Aivia, Amira, Avizo, Huygens

Image Analysis Forum



Written by: Ofra Golani, Weizmann Institute of Science and Daniel Waiger, Hebrew University of Jerusalem