Quantitative Histopathology (4 ECTS)
Universtity of Turku
This course is an introduction how to quantitate histopathological images using different image processing and analysis tools. Basic machine learning approaches for image analysis are introduced.
Entry requirements and/or target group: Master students (biosciences, biomedicine etc.) and PhD students
Learning outcomes:
After the course students
- know and understand the fundamental concepts in image processing and analysis
- know and understand how to produce and evaluate reliable quantitative data from histopathologic images
- know and understand the basics of machine learning
- understand how deep learning can be used to analyze histopathology
- are able to do simple basic image processing tasks
Content:
- An introduction to quantification of histopathologic changes in mouse models
- Basic concepts of image processing and analysis
- Basic processing and analysis of histopathological images
- Machine learning in image analysis of histopathology
Learning methods: Independent work online 108h. Online material (text + videos) including examples, quizzes, assignments
Teaching language: English
Evaluation and evaluation criteria: Passed/failed. Approved on-line exercises and assignments.
Timetable: Summer 2024, starting in 27.5.2023.
For more information, please contact Leena Strauss (leesal@utu.fi), Laura Mairinoja (lajomai@utu.fi), Pekka Ruusuvuori (pekka.ruusuvuori@utu.fi).
Please see the course in UTU study guide: BIMA3222 Quantitative Histopathology
Registration 1.4.2024-13.5.2024 in Peppi for UTU-students, and for students from ÅA or UEF with the form below until 13.5.2024:
Closed
NEW! Please note that the course is also available via open university (for others than students in UTU, UEF and ÅA)!
Enrolment for Open University studies at the University of Turku
In the registration service of Open university at the University of Turku, select the courses or modules you wish to register to. Registration time, quota and possible selection criteria are available in the course or module description in the study guide. Please also visit the course introduction page, where you will find more information on enrolment.
Open university enrolment link:
- Opettaja
Leena Strauss