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Bioimage analysis with Python

Description

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.

 

Prerequisites

  • 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
  • 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.

 

For additional information, follow this link.