Delve into image analysis and its practical application in plant phenotyping
This six-week course from the University of Nottingham will introduce you to the fundamentals of image analysis and its applications in plant phenotyping.
You’ll learn how to use imaging technologies to collect data from images and perform detailed analyses. By the end of the course, you’ll be able to extract meaningful information from image data without any destruction or harm to the subjects of your study.
Discover how to use Python programming for data analysis in Fiji
You’ll develop your skills using Fiji, also known as ImageJ.
With the help of your educators, you’ll discover how to use Python to perform simple imaging tasks in Fiji. You’ll learn from the ground up, starting with Python basics, such as if statements, for and while loops, and work your way to setting pixel values and dilating regions in code.
Learn how to use image segmentation and noise reduction for image processing
While image processing and analysis is transforming the world of bioscience, there are still significant challenges and bottlenecks to progress. One of these consistent challenges is image quality.
On this course, you’ll learn to combat poor image quality through techniques such as noise reduction and removal, image segmentation, and filtering. You’ll even learn to reconstruct 3D images and motion video in order to find meaningful data.
Study with the experts at the University of Nottingham
The educators at the University of Nottingham are experts in their field, with experience in developing novel image analysis and image-based plant phenotyping methods.
With their professional insight and guidance, you’ll be empowered to continue the evolution of plant phenotyping through image analysis.
This course is designed for researchers and professionals working in the field of plant phenotyping.
It will also be beneficial for those working in bioscience disciplines who want to learn more about image analysis and its applications.
Any software needed for the course is available to download for free and introduced as part of the course content.
