Advanced methods in bioimage analysis – Course and Conference Office

EMBL Course

Advanced methods in bioimage analysis


Proof of COVID-19 vaccination or recovery is required to attend this on-site course. Please see EMBL’s COVID-19 safety policy for on-site events.

Registration is not yet open for this event. If you are interested in receiving more information please register your interest.

Course overview

Bioimage analysis has become a keystone of biological research: the deluge of data produced by increasingly advanced microscopes calls for experts able to guide life scientists in the methods and software to be used to produce quantitative knowledge from this data. Due to the complexity of the data, without such expert guidance, it is very likely that image analysis algorithms may be applied incorrectly, possibly even producing erroneous results. Moreover, the diversity of imaging modalities, analysis algorithms and software solutions is growing so rapidly that even experts are overwhelmed. 

This advanced course concentrates on teaching cutting-edge concepts and tools for quantitative image analysis, and will seek to upgrade the competencies of future bioimage analysis experts on both theoretical algorithm advancements as well as on practical implementation skills.


This course is aimed at early-career scientists as well as staff scientists working in microscopy or image analysis facilities who already have experience in bioimage analysis. Moreover, participants should already provide or show the clear intent of providing bioimage analysis support to other researchers with less or no experience in bioimage analysis.

In selecting participants we look for scientific excellence, immediate application of the methods learned, motivation to disseminate and networking skills. We expect a solid background in bioimage analysis and at least basic programming skills.


– Microscopy image quality control and image restoration

– Advanced image segmentation and complex cell phenotyping

– Handling large microscopy images (such as whole slide scans) and big N-dimensional data 

– Neural-networks for image restoration, segmentation, and object classification.

– Co-localisation and spatial statistics

– Train the trainer: how to teach image analysis

Learning outcomes

Participants should be able to apply what they have learnt to their own image data as well as to image data of their colleagues. 

For each module, participants will learn both theoretical and practical aspects of the latest developments in the fields of bio image analysis concepts and tools. 

After this course, they are expected to be able to confidently operate and interface with a representative selection of open and closed source image analysis software, including Fiji, QuPath, ilastik, morphographX, KNIME, Imaris, and APEER, in a reproducible and shareable manner. 

In addition, participants will gain new insights about how to set up an image analysis course in their own institution.


Sponsorship opportunities

We offer a variety of event sponsoring possibilities, with the flexibility to select a set sponsorship package or combine individual sponsorship options to suit your event budget. Discounts are available for companies sponsoring multiple events at EMBL Heidelberg. View other events, or contact sponsorship@embl.de for further information.

If you are interested in becoming a media partner of this event, please visit our media partnerships webpage.


EMBL wishes to warn sponsors of EMBL conferences and courses of fraudulent schemes purporting to offer sponsorship opportunities on behalf of EMBL or affiliated with EMBL officials. One current scam campaign of which we are aware is conducted using the name ‘Judy Eastman’ (judy@gopcontact.a2hosted.com) and entails approaches to sponsors offering sponsorship opportunities on EMBL’s behalf. Please be kindly advised that all relevant communication regarding sponsorship of EMBL conferences, symposia and courses is handled by EMBL directly and is sent from an official EMBL account. EMBL does not work with any external providers on sponsorship acquisition.

Please also note that:

  • EMBL never provides attendee lists for purchase. Any offers of such are fraudulent.
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  • All payments are on invoice.

Suspicious communications purportedly from, for or on behalf of EMBL should be reported to EMBL at the following email address sponsoring@embl.de.

Date: 10 - 15 Sep 2023

Location: EMBL Heidelberg

Venue: EMBL Advanced Training Centre


  • Robert Haase
    Technische Universität Dresden, Germany
    • Anna Klemm
      Uppsala University, Sweden
      • Simon F. Nørrelykke
        Swiss Federal Institute of Technology in Zürich, Switzerland

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