IAFIG-RMS: Bioimage analysis with Python PrerequisitesNewSpecial£
THIS EVENT IS NOW FULLY BOOKED!
The aim of this 5 days course is to develop motivated participants toward becoming independent BioImage Analysts in an imaging facility or research role. Participants will be taught theory and algorithms relating to bioimage analysis using Python as the primary coding language.
Lectures will focus on image analysis theory and applications. Topics to be covered include: Image Analysis and image processing, Python and Jupyter notebooks, Visualisation, Fiji to Python, Segmentation, Omero and Python, Image Registration, Colocalisation, Time-series analysis, Tracking, Machine Learning, and Applied Machine Learning.
The bulk of the practical work will focus on Python and how to code algorithms and handle data using Python. Fiji will be used as a tool to facilitate image analysis. Omero will be described and used for some interactive coding challenges.
Research spotlight talks will demonstrate research of instructors/scientists using taught techniques in the wild.
This event is organized in collaboration with the Image Analysis Focused Interest Group and is sponsored by the Royal Microscopical Society.
The training room is located on the first floor and there is currently no wheelchair or level access available to this level.
Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.
- Cell Biologists, Biophysicists, BioImage Analysts with some experience of basic microscopy image analysis
- This course may be of interest to physical scientists looking to develop their knowledge of Python coding in the context of bioimage analysis
- This course is appropriate for researchers who are relatively proficient with computers but maybe not had the time or resources available to become programmers.
- The course is open to Graduate students, Postdocs and Staff members from the University of Cambridge, Affiliated Institutions and other external Institutions or individuals
- Please note that all participants attending this course will be charged a registration fee. Members of Industry to pay 575.00 GBP. All Members of the University of Cambridge, Affiliated Institutions and other academic participants from External Institutions and Charitable Organizations to pay 250.00 GBP. A booking will only be approved and confirmed once the fee has been paid in full.
- Further details regarding eligibility criteria are available here
- Basic awareness of Fiji/ImageJ. Some prior experience of scripting or modifying scripts would be useful (e.g. ImageJ macro scripts).
- Basic familiarity with Python. We ask that all attendees complete a basic online python coding course before the course begins. Details of this will be sent to participants prior to the course.
- In addition, we recommend either attending (See "Related courses" below), or working through the materials of An Introduction to Solving Biological Problems with Python before attending this course.
Number of sessions: 5
# | Date | Time | Venue | Trainers | |
---|---|---|---|---|---|
1 | Mon 9 Dec 2019 09:30 - 17:00 | 09:30 - 17:00 | Bioinformatics Training Room, Craik-Marshall Building | map | Dominic Waithe, Chas Nelson, Todd Fallesen |
2 | Tue 10 Dec 2019 09:30 - 17:00 | 09:30 - 17:00 | Bioinformatics Training Room, Craik-Marshall Building | map | Dominic Waithe |
3 | Wed 11 Dec 2019 09:30 - 17:00 | 09:30 - 17:00 | Bioinformatics Training Room, Craik-Marshall Building | map | Chas Nelson, Dominic Waithe, Aurelien Barbotin |
4 | Thu 12 Dec 2019 09:30 - 17:00 | 09:30 - 17:00 | Bioinformatics Training Room, Craik-Marshall Building | map | Dominic Waithe, Stephen Cross, Aurelien Barbotin |
5 | Fri 13 Dec 2019 09:30 - 17:00 | 09:30 - 17:00 | Bioinformatics Training Room, Craik-Marshall Building | map | Mikolaj Kundegorski |
Bioinformatics, Biological imaging, Data handling, Data mining, Data visualisation
As a result of attending the course, participants should be able to:
- develop pipelines of analysis which start with raw data and result in publication quality figures
The aim of this course is to:
- acquire knowledge of image analysis theory and algorithms
- consolidate and extend python coding skills relevant to bioimage analysis
- provide practical experience with, and guidance on, coding algorithm for bioimage analysis
- develop participants' confidence as independent BioImage Analysts, able to understand algorithms and apply them
- provide applied examples of the analysis from experienced analysts in the Research spotlight talks
Presentations, demonstrations, and practicals
Day 1 | Image processing and general analysis |
9:30 - 10:00 | Introduction to course and structure |
10:00 - 11:50 | Images in Python |
12:00 - 13:00 | Lunch |
13:00 - 14:30 | Interactive demonstration: image processing in Python |
14:30 - 15:00 | Tea/ Coffee break |
15:00 - 17:00 | Interactive demonstration: Fiji to Python. Visualisation |
Day 2 | Segmentation and OMERO interaction |
9:30 - 10:00 | Research spotlight talk:“Just keep swimming: Characterising motion of zebrafish" |
10:00 - 10:50 | Segmentation |
11:00 - 12:30 | Practical |
12:30 - 13:30 | Lunch |
13:30 - 14:30 | Omero and Python interfacing |
14:30 - 15:00 | Tea/ Coffee break |
15:00 - 17:00 | Practical |
Day 3 | ImageJ Interaction and Colocalization |
9:30 - 10:00 | Research spotlight talk:“Quantifying morphology from bioimages with parametric model" |
10:00 - 10:50 | Using ImageJ within Python |
11:00 - 12:30 | Practical |
12:30 - 13:30 | Lunch |
13:30 - 14:30 | Colocalisation and Registration |
14:30 - 15:00 | Tea/ Coffee break |
15:00 - 17:00 | Practical |
Day 4 | Tracking and time-series |
9:30 - 10:00 | Research spotlight talk:"Python in applied research" |
10:00 - 10:50 | Data Fitting and Time Series Analysis |
11:00 - 12:30 | Practical: time-series analysis exercises |
12:30 - 13:30 | Lunch |
13:30 - 14:30 | Tracking (e.g. cell tracking) |
14:30 - 15:00 | Tea/ Coffee break |
15:00 - 17:00 | Practical on tracking |
Day 5 | Machine Learning for Bioimage Analysis |
9:30 - 10:00 | Research spotlight talk:“Automating microscopy acquisition with deep learning” |
10:00 - 10:50 | Introduction to Machine Learning for Bioimage analysis |
11:00 - 12:30 | Practical |
12:30 - 13:30 | Lunch |
13:30 - 14:30 | BioImage analysis Applied machine learning |
14:30 - 15:00 | Tea/ Coffee break |
15:00 - 17:00 | Practical |
- All participants attending this course will be charged a registration fee.
- Members of Industry to pay 575.00 GBP
- All Members of the University of Cambridge, Affiliated Institutions and other academic participants from External Institutions and Charitable Organizations to pay 250.00 GBP.
- A booking will only be approved and confirmed once the fee has been paid in full.
- Further details regarding the charging policy are available here
5
Once a year
Booking / availability