Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

This four half day online interactive sessions are suitable for all MSD postgraduate research students and postdoctoral early career researchers involved with bright field and fluorescence microscopy.

 You are expected to attend four sessions:

  • Monday 2 December, 09:30 - 12:00
  • Tuesday 3 December, 09:30 - 12:00
  • Wednesday 4 December, 09:30 - 12:00
  • Friday 6 December, 09:30 - 12:00

COURSE AIM

This course consists of four 2.5 hour live interactive online sessions that aims to provide the basic skills necessary to tackle the most common image analysis tasks. Attendees will be shown a variety of techniques and worked examples. They will also learn where and how to access additional help in the future.  

At the tutor’s discretion, some of the scheduled sessions may run into the afternoon if extra time is needed.

COURSE CONTENT

This course will cover the following topics:

  • How to interact with the Fiji/ImageJ interface and functions
  • The basic approaches to segmentation and intensity measurements in 2D and 3D
  • How to manage measurements through curating regions of interest
  • How to use image filtering
  • How to perform colocalisation analysis
  • Recommended plugins and image analysis tools
  • How to keep Fiji/ImageJ up-to-date and how to install plugins.
  • How programming and scripting works in Fiji/ImageJ
  • How to use machine learning for image segmentation and de-noising
  • Best practise with regards to microscopy image analysis and how to avoid common pitfalls
  • Where to find online resources for continued development

COURSE OBJECTIVES

 At the end of the course, participants will be able to

  • Interact with the Fiji/ImageJ interface and functions
  • Understand the basic principles of Image Analysis and apply them to their images
  • Use machine learning for image segmentation and de-noising
  • Undertake programming and scripting in Fiji/ImageJ
  • Keep Fiji/ImageJ up-to-date and install plugins.

PARTICIPANT NUMBERS

 30

FEEDBACK FROM PREVIOUS ONLINE SESSION

"Excellent instructor and course content. Really enjoyed Lior's teaching and supportive manner. I learnt a lot of very applicable tools that I will apply to my research. I will be recommending it to my colleagues."

"This workshop is indeed the best so far I have attended not only it’s useful but it’s also well organized and presented. Moreover, we have time for practising! This helps a lot. Thanks a lot!"

"I thought the course was very well explained and I found everything easy to understand. I hadn't had any previous experience with image analysis before this course so thank you Lior."

ATTENDANCE CERTIFICATE ON SURVEY COMPLETION

It is now a requirement that you complete the three short questions in the survey you receive after attending the course. Once you have submitted the survey, you will be sent an email with a link to your attendance certificate. This is to ensure we receive the feedback we need to evaluate and improve our courses. Survey results are downloaded and stored anonymously.