The BioImage Informatics facility is our favorite image analysis facility at ScilifeLab! 🙂
Please spread the word! 🙂
You can join the Switzerland’s Image and Data Analysis School, ZIDAS 2021.
This one-week school provides a hands-on introduction to image processing and analysis, with an emphasis on biologically relevant examples.
This school is for you if…
* you are a life-science researcher with a pressing need to quantify your light-microscopy images.
* you are uncertain about how to: Best calculate co-localisation, do deconvolution, automate the counting of cells, track objects over time, handle massive amounts of image data, record your image-analysis workflows in a reproducible manner.
More information can be found here: https://2021.zidas.org/
Check out the Nikon Artificial Intelligence (NIS.ai) webinar series to understand how Ai can help you in your microscopy experiments.
The NIS.ai Webinar Series will take place on Tuesdays at 14:00hrs and we are delighted to announce the first two talks:
Program and free registration: here.
Artificial Intelligence, Deep Learning and Neuronal Networks are taking over the world, including microscopy. Within the next couple of years, you might well end up wondering how you got anything done without them!
Having an idea how Artificial Intelligence, Deep Learning and Neuronal networks work means that you will be able to come up with ideas about how they can help you in your research.
The Neubias (Network of European image bioanalysts) webinars and meetings are a good place to learn.
Here are 2 upcoming webinars about tools to train and use AI algorithms.
Lots of interesting courses and webinars about microscopy in these corona times. The BioImage Informatics facility at Scilife will present how useful it is to build imaging pipelines with Fiji/imageJ.
April 6th, 10:00-11:00: “ImageJ/Fiji – Make Your Own Macros – Overview”. This is not to teach how to script but to give you an overview of the scripting possibilities in ImageJ/Fiji. Please register here.
Version 2.0 of TissUUmaps is now released: TissUUmaps allows fast interactive display of tissue slide images and uses an overlay to display any sort of marker data on top. Be it spatially resolved gene expression, per cell data, or regions of interest. TissUUmaps is developed in the Wählby-Lab, with involvement of BIIF, and was first published in https://doi.org/10.1093/bioinformatics/btaa541.
Try out TissUUmaps and interact with a in-situ-sequencing dataset on a brain slice!
Advanced Methods in Bioimage Analysis, Online EMBO Practical Course, 26 Jun – 2 Jul 2021; Registration Deadline: 5 Apr 2021
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. BIIF is part of the scientific organization team. Register here.
Global BioImaging-ZEISS webinar series in Light Microscopy
Check here to see some nice general microscopy webinars by Global Bioimaging, the global pendant to Euro Bioimaging:
As usual the lectures at the LCI microscopy course will broadcasted live online, free of charge and there is no need to register.
Title: Microscopy: improve your imaging skills – from sample preparation to image analysis
The aim for this course is to improve the microscopy skills of students and researchers who have already used a microscope to acquire digital images of fluorescent samples but feel that more knowledge could help them.
Applications are closed but all lectures will be broadcasted live and open to anyone without registration.
The course covers the following topics:
Check the course schedule and details of how to join the Zoom webinars. Scroll down to read the kind testimonies of our dear students! 😊
Here is the course syllabus.
Hope you enjoy the LCI facility microscopy course 2021!
Congratulations to our dear in-house image analyst Gisele Miranda who got the prestigious Chan Zuckerberg Initiative grant in December! 🙂
Gisele got this grant thanks to the fruitful collaboration between the BioImage Informatics facility at Scilife and the Live Cell Imaging facility at KI. We are delighted for her and for all the LCI users as this will allow us to keep working with Gisele for many years.
Congratulations Gisele! Very well-deserved! 🙂
Look at what CZI has chosen as their symbol of Science: a microscope!
God fortsättning everyone! Happy New Year! 🙂
Neubias is back with great image analysis/handling webinars!
Here are 5 webinars with interesting information about how to handle Big Data.
CLIJ2 allows you to use ImageJ/Fiji on GPU instead if CPU processing, so much faster! 🙂
Here is a nice article about what CLIJ2 can do. By the way, this article is published on a new imaging forum called FocalPlane. Check it out! And here is the presentation of how to use CLIJ2 at one of the recent Neubias event in May 2020.
If you have an analysis pipeline built in Fiji, Icy or Matlab and processing takes a long time, CLIJ2 will help you a lot.
Updates on the next events of the NEUBIAS Academy@Home Webinar series,
Newly confirmed events:
5 May: ilastik beyond pixel classification, by Anna Kreshuk and Dominik Kutra-
6 May: GPU-Accelerated Image Processing with CLIJ2, by Robert Haase
7 May: Interactive Bioimage Analysis with Python and Jupyter, by Guillaume Witz
Upcoming events open to registration:
LAST CHANCE TO REGISTER:
28 April: Introduction to nuclei segmentation with StarDist, by Martin Weigert et al
29 April: Quantitative Pathology and Bioimage Analysis: QuPath v0.2.0, By Pete Bankhead
30 April: Advanced Image Processing with MorphoLibJ, by David Legland
Two weeks after the opening of the Academy and of the registrations, Webinars and online courses have already attracted over 5,000 registrations!
The events are recorded and some are already available on the Youtube NEUBIAS Channel.
Furthermore, a thread will be opened in the image.sc Forum to report Q&As and to welcome further questions/comments for each event.
You’ll find more information here.