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Image processing
Provider: Faculty of Health and Medical Sciences

Activity no.: 3645-19-00-00There are no available seats 
Enrollment deadline: 14/05/2019
Date and time14.06.2019, at: 08:00 - 21.06.2019, at: 16:00
Regular seats12
Course fee10,440.00 kr.
LecturersClara Prats
ECTS credits5.50
Contact personIda Marie Bergman Rasmussen    E-mail address: ida.mbr@sund.ku.dk
Enrolment Handling/Course OrganiserPhD administration     E-mail address: phdkursus@sund.ku.dk

Aim and content
This course is free of charge for PhD students at Danish universities (except Copenhagen Business School), and for PhD students at graduate schools in the other Nordic countries. All other participants must pay the course fee.

Anyone can apply for the course, but if you are not a PhD student, you will be placed on the waiting list for the course until enrollment deadline. After the deadline of enrollment, available seats will be allocated to students on the waiting list.

Learning objectives
A student who has met the objectives of the course will be able to:

1. This course is an introduction to image processing and analysis, with a focus on biologically relevant examples.

2. The students will learn the fundamentals of image analysis while learning how to use open source tools (Fiji and Ilastik).

3. The student will learn how to do basic Macro programming in Fiji (ImageJ) for automated batch analysis of images.

We will initially use FijJi to illustrate fundamental image analysis concepts, then expand to introduce other software packages such as cell profiler and Ilastik.

The students will learn what a digital image is, how and when to perform basic image processing tasks and how to combine such tasks to perform advanced image processing and segmentation, automated pixel classification and, 2D and 3D measurements. Furthermore, the student will learn basic Macro programming and how to automate analysis of many images.

Students will have to submit an image processing project before the course; summarizing a bioimaging experiment and describing the research question.

The course will consist of a course preparation day (June 14th - introduction to image formation, basics on Fiji and preparation of own projects) followed by 5 days teaching (June 17-21st). The course program includes work on own project sessions with advice, supervision and support from the teachers (3 at least at all times). Within 1 week after the course, students will need to submit a course report based on the outcome from their own project.

All participants are expected to bring their own laptop, which should meet the following requirements:

1) A minimum of 2 GB main RAM

2) A graphic board compatible with Fiji 3D viewer*

3) At least 10 GB available on the system partition

4) The ability to connect to internet through WIFI

5) A USB 2 or USB 3 port.

* To test if your graphic board is compatible with Fiji 3D viewer: call File > Open samples > Fly brain and Plugins > 3D viewer. Use the default settings of the 3D viewer and press "OK". You should see the 3D rendering of the image stack and also be able to interact with the volume with the mouse.

12 PhD students who use digital imaging.

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


Lectures are combined with hands on exercises

Course director
Clara Prats; cprats@sund.ku.dk

Chong Zhang (Univeristat Pompeu Fabra, Barcelona Spain)
Fabrice Cordelieres (University of Bordeaux)

Assistance from
Pablo Hernandez Varas
Thomas Braunstein
Clara Prats

Course secretary
Ida Marie Rasmussen; idambr@sund.ku.dk

14.06.2019, 17.06.2019 – 21.06.2019

Course location
Maersk Tower, Panum

Please register before May 14 2019

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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