BioImage Informatics

The BioImage Informatics Unit provides the support and training you need to perform state-of-the-art analyses on your image data. Our experts can help you deploy computational methods using computer vision, machine learning, and bioinformatics to analyze your images – see examples on our project database. Whether you are looking for training on how to use existing software solutions or help developing a custom workflow, we can help you get your analysis running.

There are many ways to contact us! Write us an email, join one of the weekly NBIS drop-ins, or fill-out the NBIS support form. We usually respond fast and are always open to new ideas. You can also visit us at one of our two locations: at the SciLifeLab Solna campus, or at the Centre for Image Analysis in Uppsala.

BIIF is a unit of the National Bioinformatics Infrastructure Sweden NBIS, with funding from SciLifeLab, National Microscopy Infrastructure NMI (VR-RFI 2019-00217), and the Chan-Zuckerberg Initiative. We are active within the GloBIAS and EuroBioImaging networks.

project website: biifsweden.github.io
biif@scilifelab.se

SERVICES

• Advice on best-practice and guidance on overall experimental design (staining, sample preparation, and image acquisition) for research involving microscopy imaging and quantitative data analysis.
• Guidance on image analysis assay development, including image processing algorithm development and software engineering to address challenging project goals.
• Advice on best-practice and guidance on high throughput/large-scale image processing using computing clusters, including data transfer and storage during the activity of the project.
• Guidance on large-scale data analysis and visualization.
• Dissemination of bioimage analysis knowledge in courses and workshops.
• The AIDA data hub offers Data Sharing, Policy Support, and Services for researchers in Swedish medical imaging AI, and operate the currently largest national AI research system for sensitive personal data in Sweden.

Here is a collection of ongoing and completed projects supported by the BioImage Informatics Unit.

We regularly send out a newsletter informing about upcoming events, workshops, and other relevant information. You can also follow us on X @biif_sweden .

Open Positions

We open positions @BIIF! Please contact us if you have any question about the positions.

A permanent bioinformatician position (6-month trial period) located at Uppsala University, Department of Computer Science. More information here.

Research Software Engineer position located at our KTH site in Stockholm Solna.
This is a 1-year position, but there is a possibility to extend it to a permanent position after. More information here.

3-year Postdoc within Arise2 – primarily at EMBL-Heidelberg (Christian Tischer). Aim is to develop scalable and reusable analysis pipelines for spatial omics. More information here.

Weekly Drop-In Support

Our weekly drop-ins are open for anyone doing academic research with questions about bioimage informatics. Are you planning a new project? Are you stuck or a second pair of eyes in some part of your analysis? Do you need help choosing the right bioimage analysis tool? We are happy to answer questions, small or large.

You can find us as part of the weekly NBIS drop-in sessions over Zoom, as well as on site in Stockholm. Read more about the NBIS drop-in here.

NEWSLETTER

In our newsletter we inform about upcoming courses on bioimage analysis, services of BIIF, and other useful information about bioimage analysis. Just fill-out this google form if you want to be added to our mailing list. You can also read the newsletter online.

COURSES AND WORKSHOPS

Part of our research support is provided in the form of courses, workshops and invited talks at courses related to digital image processing and analysis in life science.

Upcoming events:

Together with Frederic Ballllosera Navarro from Emma Lundberg’s group, we are participating with a workshop on Multiplexed tissue imaging: tools and approaches to the Images to Knowledge (I2K) conference.

Courses and Seminars we are involved in:

NBIS workshop in Neural Nets and Deep Learning

This course gives an introduction to the concept of Neural Networks (NN) and Deep Learning. Topics covered include:

• NN building blocks, including concepts such as neurons, activation functions, loss functions, gradient descent and back-propagation
• Convolutional Neural Networks
• Recursive Neural Networks
• Autoencoders
• Best practices when designing NNs

More information here.

Spatial Omics Data Analysis

BIIF within NBIS (National Bioinformatics Infrastructure Sweden) and with the Human Developmental Cell Atlas is organizing a workshop on Spatial Omics Data Analysis. The workshop provides resources to advanced tools for analysis of spatial datasets via a series of online lectures and computer exercises. More information here.

EMBO Practical Course: Advanced methods in bioimage analysis

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

More information here.

Digital image analysis for scientific applications

This course aims at giving doctoral students and researchers from different disciplines sufficient understanding to solve basic computerized image analysis problems. The course offers an introduction to a number of freely available software tools, preparing the participants to start using computerized image analysis in their own research.

More information available here.

LCI microscopy course – From sample preparation to image analysis.

This course provides you with enough theoretical and practical knowledge so that you are able to fully understand how to properly use the hardware and software on your own microscope. It also teaches the principles of image analysis. A dedicated workshop on participants’ data gives an understanding on which questions can be addressed using image analysis. Lectures are broadcasted live on Zoom! More Information: LCI course

Introduction in Image analysis for Life science, Graduate course, CCI, Göteborg

The focus of the course is on reaching a broad understanding of computerized image analysis in Life Science (mainly fluorescence and electron microscopy images) and a basic understanding of the theory and algorithms behind the image analysis methods and tools. Hands-on exercises that will teach a broad functionality of these tools and the concepts needed for building suitable workflow for a given application. More information on the CCI course website.

BIIF YouTube channel

On the BIIF YouTube channel we upload tutorials on bioimage analysis tools: link

GloBIAS seminar series

We are involved in the organization of GloBIAS, and their seminar series: link
GloBIAS continues the activities of NEUBIAS, the network of european bioimage analysts. A rich selection of bioimage webinars were made available online on the NEUBIAS Youtube channel. There you will also our video on ImageJ/Fiji Macro Scripting link.

NBIS Long-term Support

The NBIS Bioinformatics Support Peer Review track (WABI) strives to enable excellent and Data-Driven Life Science, by ensuring that peer-reviewed research projects have access to advanced bioinformatics and data science competence. This support has been enabled by the SciLifeLab & Wallenberg Data Driven Life Science Program and the Knut and Alice Wallenberg Foundation. The idea is simple: A senior bioinformatician will work in your project 500 hours for free! Hands-on involvement by the applying research group is required to ensure efficient knowledge transfer.

More information here .