CROSS INSTITUTIONAL BIOIMAGING PHD COURSE
September 9 - November 25(Deadline: August 1)
Next time: Fall semester 2019, 9 lectures
Locations: Copenhagen, Odense, Århus, Kng. Lyngby. (Transportation expenses are not covered by the course)
Level of course: PhD course
No. of contact hours 80
Capacity limits: 20
10 ECTS points
|Monday September 9||Fluorescence Microscopy, two photon and Image Analysis||SDU|
|Monday September 16||Confocal Microscopy||KU|
|Monday September 23||Non-invasive imaging modalities (PET-SPECT-CT-R)||SDU/OUH|
|Monday September 30||Live imaging in yeast, plants and mammalian cells||KU|
|Monday October 7||Image Analysis||KU|
|Monday October 21||Single particle & Fluorescent Proteins||AU|
|Monday October 28||Super-resolution, STED, ICS and Raman||SDU|
|Monday November 4||Image analysis||DTU|
|Monday November 11||EM||KU|
|Monday November 18||Preparation for the exam||Home 🙂|
|Monday November 25||Evaluation and Student Talks||KU/SDU|
Objectives of the course:
The Cross Institutional Bioimaging Ph.D. course is interdisciplinary and cross-institutional and will be given by a series of lecturers who are experts within each their field of bioimaging. The course will take place at different institutions in order to expose the students to different research groups, their researchers and experimental research facilities. The course will thus give the students a unique opportunity of orienting him or herself within an active and diverse field of interdisciplinary science within bioimaging.
The course is relevant for PhD students within medicine, physics, chemistry, biochemistry, molecular biology, nano-bioscience, pharmaceutical sciences, agricultural science or biology. The emphasis of the course is a tour of all bioimaging techniques available in Denmark and will cover subjects like live cell imaging, spinning disk microscopy, electron microscopy, photoactivated localization microscopy, single particle techniques, structured illumination, stimulated emission depletion microscopy, imaging of neurons and cell migration.
Preliminary time schedule for the course in 2019:
The course starts September 9th 2019, and consecutive Mondays for 10 weeks at 4 different universities and by different lecturers. Each day of the course covers around 8 hours, from 09:30-17:30. In general, the morning session will consist of a set of lectures and the afternoon session will predominantly involve either the student’s active participation in experiments, specific numerical exercises, or inspection of the local experimental facilities.
Course credit and evaluation
The workload of the course corresponds to 10 ECTS points (under approval at PhD committee at SDU at the moment), the total workload includes reading material for each lecture and the preparation of the final talk (presentation). Credit for the course requires the student’s presence at 8 of 10 lectures. For missed lectures students will have to write 3 page reports on the topic of the missed lecture. Also the students presence on the exam is mandatory.
The course is evaluated with: Internal oral examination with co-examiner assessed passed/not passed at KU and SDU depending where for students it is more convenient. 20 minutes presentation of a project and 15 minutes questions from examiners and from a student opponent. Each student has to be an opponent for one presentation of another student. In the presentation each student has to present a description of an experiment using one of the applications described in the course and include an image analysis strategy. The task for the presentation will be given in advance (on the last lecture day the 11th of November).
In order to get credits for the course, every student has to be present at all the other students’ talks in their session (at KU / SDU) on the exam day.
Registration and transportation: Registration is open by email to
PhD course for students with Master Degree in Physics, Engineering, Life Science, Biology, Medicine Accepted at a PhD program
Eva Arnspang Christensen and Jonathan Brewer (SDU)
(AU) Lene Niemann Nejsum, Morten Nielsen, Victoria Birkedal
(DTU) Rasmus Reinhold Paulsen, Anders Nymark Christensen, Anders Bjorholm Dahl
(KU) Clara Prats, Klaus Qvortrup, Sune Darkner, Jon Sporring, Alexander Schulz, Michael Lisby, Ivana Novak
(SDU) Eva Arnspang Christensen, Martin Hedegaard, Jonathan Brewer, Helge Thisgaard , Daniel Wüstner
Will be announced every week during the course.
All materials will be published on the open black board platform (SDU).
If you have any questions, please contact Vita Solovyeva, Email:
Short lecture description
Electron microscopy: Klaus Qvortrup
The course provides an introduction to the essential grounding in the basic principles of electron microscopy, covering topics such as electron optics, electromagnetic lenses, principles of transmission and scanning electron microscopy, electron sources, vacuum systems, specimen-electron interactions and diffraction. The state-of-the-art facilities available at CFIM allow for a strong practical element of demonstrations of both cryo- and room temperature electron microscopy. The course will be run by experienced microscopists in a relaxed atmosphere with the aim of promoting discussion and exchange of ideas between students and tutors.
Single particle & Fluorescent Proteins: Morten Nielsen
In this lecture we will focus on how to study receptor trafficking using imaging technologies. We will go through methods to follow endocytic receptors from the surface and through the endo-lysosomal system and demonstrate how we analyse if receptors are transcytosed in polarised endothelial and epithelial cells.
Confocal Microscopy: Clara Prats
Students will be introduced to the Principles and Essentials of Single Point Scanning Microscopy. Lectures and hands-on practical exercises will be combined to teach the students the critical components of a Confocal Microscope and, how to properly construct imaging light paths and settings to avoid artifacts and collect proper bioimaging data
Non-invasive imaging modalities (PET-SPECT-CT-R): Helge Thisgaard
The course will cover the basics concepts of preclinical nuclear medicine techniques using PET/SPECT/CT imaging modalities. The theory behind the techniques will be presented followed by hands-on experience in the laboratory.
Fluorescence Microscopy, two photon and Image Analysis: Jonathan Brewer & Eva Arnspang Christensen
Photoactivatable localization microscopy (PALM) is a recent developed technique which is optimal for membranes. It takes benefit from activating a subset of the fluorophores at each timepoint in the sample and reconstituting the full image from mapped positions in a series of images. K-space image correlation spectroscopy is a technique in which the bulk diffusion coefficient is calculated after conventional epi fluorescence or TIRF imaging.
Image Analysis: Jon Sporring, Sune Darkner
Image Analysis: Rasmus Reinhold Paulsen, Anders Nymark Christensen, Anders Bjorholm Dahl
The image analysis course at DTU Compute is focused on two topics that are relevant for biomedical image analysis. The first topic is pixel classification, where the goal is to assign a relevant label to a given pixel. Labels are normally predefined like for example background, nuclei, and membrane. The classification is based on a using a training set of images to create a statistical assumption on the distribution of pixel values within the classes.
The second topic is BLOB analysis, where the goal is to classify objects in an image based on their shape. Typical examples are nuclei detection in cell images or organ identification in medical scans.
Super-resolution, STED, ICS and Raman: Eva Arnspang Christensen, Daniel Wüstner, Jonathan Brewer & Martin Hedegaard
Confocal Raman imaging is a label free imaging technique based entirely on molecular vibrations. This course will include an introduction to basic working principles and choice of instrumentation including lasers, microscopes and spectrometers. In addition, there will be an introduction to pre-processing and analysis of Raman imaging data.
Live imaging in yeast, plants and mammalian cells: Ivana Novak, Michael Lisby, Alexander Schultz