Graduate School of health and Medical Sciences

Python for Bioimage Analysis
Provider: Faculty of Health and Medical Sciences

Activity no.: 3701-25-00-00	There are 6 available seats
	Enrollment deadline: 01/03/2025

Date and time	31.03.2025, at: 09:00 - 02.04.2025, at: 17:00
Regular seats	15
Course fee	5,640.00 kr.
Lecturers	Clara Prats
ECTS credits	2.50

Contact person	Jacqueline van Hall E-mail address: jacq@sund.ku.dk

Enrolment Handling/Course Organiser	PhD administration E-mail address: phdkursus@sund.ku.dk

Aim and content This is a generic course. This means that the course is reserved for PhD students at the Graduate School of Health and Medical Sciences at UCPH. Anyone can apply for the course, but if you are not a PhD student at the Graduate School, you will be placed on the waiting list until enrollment deadline. After the enrolment deadline, available seats will be allocated to the waiting list. The course is free of charge for PhD students at Danish universities (except Copenhagen Business School), and for PhD students at NorDoc member faculties. All other participants must pay the course fee. Learning objectives A student who has met the objectives of the course will be able to: 1. Run simple python scripts for automating image analysis. 2. Understand the principles of image processing and apply appropriate image processing operations to their images using the python library scikit-image. 3. Use machine learning to classify pixels, objects and images, and gain insight into how such methods work. 4. Extract regions of interest from their own data and measure relevant properties. Content Python scripting provides a general and flexible toolset for researchers to quantify and analyse digital images acquired from microscopy or clinical imaging. It enables researchers to automate image processing and connect their workflows with downstream processes like statistical testing and data visualisation. The course begins with an introduction to basic python programming and uses image data to familiarise students with core programming concepts (e.g. conditionals, loops and functions) in a research-relevant manner. Students will learn to use popular python libraries such as scikit-image, matplotlib and napari to visualise, interact with and extract quantitative data from such digital images. Over the course, students will gain insight into what a digital image is, how various image processing operations work and when to perform such operations. They will learn how to segment images (identify object of interest in their images), using classical programming methods as well as machine learning solutions. Finally, students will be able to measure biologically interesting properties such as quantity, intensity, or morphology of their objects of interest. Participants PhD students who use microscopy in their research projects, and who would like to learn image analysis methods for extracting quantitative information from their image data in an automated and reproducible way. Relevance to graduate programmes The course is relevant to PhD students from the following graduate programmes at the Graduate School of Health and Medical Sciences, UCPH: All graduate programmes Language English Form Each day of the 3-day course will consist of lectures (taught either by local teachers or remote guest lecturers), followed by in-class practical exercises and discussions facilitated by local classroom teachers. On the last day, students will from groups to train or fine-tune a deep-learning network and present their group’s results to the class. Students will be expected to download and install relevant software packages (sent in course instructions) on to their personal computers before the start of the course. Course director Clara Prats, Assoc. Prof., University of Copenhagen, cprats@sund.ku.dk Teachers Richard De Mets, PhD, University of Copenhagen Tricia Loo, PhD, University of Copenhagen Peidi Xu, PhD, University of Copenhagen Julia Katharina Mertesdorf, MSc, University of Copenhagen Sébastien Tosi, PhD, Universitat Pompeau Fabra Chong Zhang, PhD, IRB Barcelona Dates 31st March – 2nd April 2025 Course location University of Copenhagen, Panum Institute Registration Please register before 1 March 2025. Expected frequency N/A Seats to PhD students from other Danish universities will be allocated on a first-come, first-served basis and according to the applicable rules. Applications from other participants will be considered after the last day of enrolment. Note: All applicants are asked to submit invoice details in case of no-show, late cancellation or obligation to pay the course fee (typically non-PhD students). If you are a PhD student, your participation in the course must be in agreement with your principal supervisor.

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