Bioimage analysis with Python

The aim of this 5 days course is to develop motivated participants toward becoming independent BioImage Analysts in an imaging facility or research role. Participants will be taught theory and algorithms relating to bioimage analysis using Python as the primary coding language.

Lectures will focus on image analysis theory and applications. Topics to be covered include: Image Analysis and image processing, Python and Jupyter notebooks, Visualisation, Fiji to Python, Segmentation, Omero and Python, Image Registration, Colocalisation, Time-series analysis, Tracking, Machine Learning, and Applied Machine Learning.

The bulk of the practical work will focus on Python and how to code algorithms and handle data using Python. Fiji will be used as a tool to facilitate image analysis. Omero will be described and used for some interactive coding challenges.

Research spotlight talks will demonstrate research of instructors/scientists using taught techniques in the wild.

This event is organized in collaboration with the Image Analysis Focused Interest Group and is sponsored by the Royal Microscopical Society.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.


As a result of attending the course, participants should be able to develop pipelines of analysis which start with raw data and result in publication quality figures.


The aim of this course is to:

  • acquire knowledge of image analysis theory and algorithms
  • consolidate and extend python coding skills relevant to bioimage analysis
  • provide practical experience with, and guidance on, coding algorithm for bioimage analysis
  • develop participants’ confidence as independent BioImage Analysts, able to understand algorithms and apply them
  • provide applied examples of the analysis from experienced analysts in the Research spotlight talks

Target audience

  • Cell Biologists, Biophysicists, BioImage Analysts with some experience of basic microscopy image analysis
  • This course may be of interest to physical scientists looking to develop their knowledge of Python coding in the context of bioimage analysis
  • This course is appropriate for researchers who are relatively proficient with computers but maybe not had the time or resources available to become programmers.
  • The course is open to Graduate students, Postdocs and Staff members from the University of Cambridge, Affiliated Institutions and other external Institutions or individuals
  • Please note that all participants attending this course will be charged a registration fee. Members of Industry to pay 575.00 GBP. All Members of the University of Cambridge, Affiliated Institutions and other academic participants from External Institutions and Charitable Organizations to pay 250.00 GBP. A booking will only be approved and confirmed once the fee has been paid in full.
  • Further details regarding eligibility criteria are available here


  • Basic awareness of Fiji/ImageJ. Some prior experience of scripting or modifying scripts would be useful (e.g. ImageJ macro scripts).
  • Basic familiarity with Python. We ask that all attendees complete a basic online python coding course before the course begins. Details of this will be sent to participants prior to the course.
  • In addition, we recommend either attending (See “Related courses” below), or working through the materials of An Introduction to Solving Biological Problems with Python before attending this course.

How to book?

Please visit the University of Cambridge training pages to book a spot on this course.

Chas Nelson
Chas Nelson
LKAS Research Fellow in Data Science

Interdisciplinary scientist with a background in bioimaging and informatics.