Image Analysis
Processing and analysing images with Python for Biologists
An image speaks a thousand words, or so they say. And it's true, bioimaging can produce amazing amounts of data and, with processing and analysis, great biological insights. Traditionally the number of images was small and much analysis was qualitative; however, scientists are now working with increasingly larger and more complex imaging datasets and focussing on quantitative analyses. Modern programming is essential to fully benefit from and automate data analysis.
Image analysis in Python leverages both well established and state-of-the-art statistical and modelling methods, some of which are available as soon as a paper is published! This intensive, hands-on, one-day course will teach you the basics of image processing, analysis and figure creation using Python and is a natural follow on for those who have done our Data Exploration course (see prerequisites below).
What does the course cover?
Images in Python
The first part of the course will introduce how Python can handle and manipulate images as n-dimensional numpy arrays and how basic image processing can be done using the scikit-image package, e.g. transformations, simple segmentation and simple image measurements.
This part of the course will include plenty of time to explore example data as we introduce you to the napari library for interactive image viewing.
Analysing Images
The second part of the course focusses on two commonly encountered image analysis tasks in biology - segmentation and tracking. We will introduce the concepts behind these tasks and how they can be achieved using Python before demoing some of the latest deep learning solutions.
Attendees will then have the opportunity to work on an extended practical task tracking elements within real biological data and producing high quality figures and results.
Who is the course for?
Scientists at any career stage (including students) in biology and related areas of science and medicine who have some experience of coding in Python (see prerequisites) and wish to expand their skills in the area of image processing and analysis. Some basic image handling knowledge is assumed (see notes on prerequisites).
If you have no experience programming in any language then you may find our Python for Biologists course more appropriate.
Attendees usually work on their own laptops and are expected to install some programmes before the course. Any laptop or operating system is suitable.
A note on prerequisites
We expect attendees to have previous Python skills equivalent to having done our Data Exploration course and built upon those skills after the course.
This means that participants should be comfortable:
- installing applications and python modules on their own laptops
- reading and writing data into numpy arrays
- manipulating numpy arrays (indexing, slicing, etc.)
- using numpy and scipy for simple mathematics and data analysis, e.g. calculating mean or running linear regression
- using seaborn and matplotlib for visualising data