Introduction to Image Analysis Software (IAS) 2024 October, 1.5 hp
| Course number | 14,1 |
| Year | 2024 |
| Type | Methodcourse |
| Track | - |
| Max participants | 9 |
| Application deadline | 2024-10-01 |
| Language | En |
| Course leader | Jeremy Adler |
| Department | Department of Immunology, Genetics and Pathology |
| Visiting address | Dag Hammarskjölds väg 20 |
| Post address | Rudbeck Laboratory, SE-751 85 Uppsala |
| Dates | October: 17,18 & 22,23,24 |
| Location | Rita Levi Montalcini room, RudbeckLab |
| Course length | 5 days , 0930-1700 |
| Course report | |
| Course plan | Course plan |
Description
Acquiring images is not the final step - need measurements.
The aim is to discover the power of image analysis and become proficient in using the Fiji version of ImageJ and Cell Profile – both open source.
The course is highly interactive, learning about image analysis and the specifics of the software by working with images, finding and solving problems.
At the end of the course students will create an image analysis sequence to address a problem relevant to their own work.
No prior experience of image analysis or software is necessary.
Learning outcomes
To understand the potential of image analysis, the language used and appreciate the practical problems.
Students will be able to use standard software to automatically analyze images and understand the importance of acquiring images of the quality required for the analysis.
Contents
Learn about image analysis with an in depth examination of ImageJ and workflows using ImageJ macros.
Other popular/useful software will be introduced:
Huygens to improve resolution
Cell Profiler to create pipelines for automated analysis of cells
QuPath to quantify the very large datasets generated by slide scanners.
Instructions
The course is restricted to 9 applicants.
Applications will be assessed 1 month before the start of the course and applicants notified.
Examination
To receive the 1.5hp all sessions must be attended.
At the end of the course each student will present a project to the class; describing the problem and demonstrating their solution.
Literature
Teaching staff
Lecturer:
Jeremy Adler (BioVis)
Anna Klemm (SciLifeLab BioImage Informatics Facility)
More information
Jeremy Adler
BioVis Platform, Uppsala University
Dag Hammarskjölds väg 20,
Rudbeck Lab
SE-751 85 Uppsala, Sweden
jeremy.adler@igp.uu.se
Phone 070-1679349