Training

CAMDU offers a range of training and workshop opportunities. Book on to a future training course or explore our resources for independent learning below.

Book on to a training course

7th December - Introduction to OMERO.web 10-11th December - Image Analysis in Fiji and Python

Don't see a training sessions you'd like? Please email to register your interest.

Image Analysis

Beginner's guide to Fiji/ImageJ:

Excellent guide to Fiji available here written by Cameron Nowell. Includes how to setup Fiji, opening images, adjusting brightness/contrast, scale bars, colour channels, opening different image formats, simple analysis (e.g. intensity measurements and cell counting), batch processing, and more complicated analysis. Also available here as a PDF.

Watch an Introduction to Image Analysis:

Laura's lecture from 2024. Introduces image analysis and programming in Fiji.

Image Analysis Worksheets

Self paced worksheets for learning image analysis in Fiji

Introduction to Python with Napari:

The aim of this course is not to teach python, but to give you an idea of how it can be used for image analysis.
To get started:

Everyone: Download and unzip this folder (make sure you know where you've saved it) or you can clone the git repository
Beginner Python users: I recommend installing AnacondaLink opens in a new windowLink opens in a new window. After installing please follow the step by step instructions in AnacondaSetup.pdf.
Experienced Python users: Set up a virtual or conda environment with Python 3.9. Within the environment please install napariLink opens in a new windowLink opens in a new window (I use python -m pip install napari[all], check the instructions for your operating system if you have issues). I use jupyter notebooks but you can use your favourite IDE instead. After activating the environment, please check you can run the SetupCheck.py script (or SetupCheck.ipynb if using jupyter notebook) from the attached .zip folder.

You should get a Napari window that opens and looks like the picture SetupCheck.png.

Follow along with the training notebook typing and running the commands in the cells (use shift + click to run the cells)
To learn more about image analysis with python, take a look at Neubais bioimage analysis with python course

Attempt the CAMDU Challenge in Fiji or Python:

Consolidate your skills by trying them out on this challenge. Download the data set provided. The data set contains six microscopy images (.tif files), each with three channels: in the first, you have a a GFP-tagged protein of interest, which forms foci; on the second a cytoplasmic marker; and on the third a brightfield image of the cells.

You can try to write a code to do one or all of the following:

Identify the cell boundaries (channel two only, use only the most in focus plane)
Detect the foci (channel one only, use a maximum projection)
Count the foci in specific cells - combining the first two codes
Create a code to batch process all the files in the data set.

Watch Demonstration Videos on topics related to Image Analysis and Computing

Short videos covering a number of different topics and softwares

Post on image.sc forum:

Ask for help from experts from all over the world by posting on the image.sc forum

Data Management

Warwick Medical School