Image analysis – Page 2 – The Live Cell Imaging facility

The LCI microscopy course 2021 starts next week! :)

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:

Optics, image formation, fluorescence, fluorophores, microscope and microscopy types
Objectives and refraction index, Cameras and detectors
Noise and background, Cameras and detectors, Bit depth and saturation, Multicolour imaging
Resolution and contrast, Sample preparation, Immunostaining
Nyquist sampling, Confocal and wide field settings, Scaling up and speeding up, High throughput/content
Volume imaging, deconvolution, multiphoton, Clearing and expansion
Live cell imaging, Fourier, AI, Super Resolution microscopy
Data handling, OMERO.figure, Requirements for image analysis, Colocalization
Image processing and analysis

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!

Gisele got the Chan Zuckerberg Initiative grant!!

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!

5 webinars on Big Data

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: Open Computing Language and ImageJ2, GPU power for everyone

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.

Neubias webinars on Youtube

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.

Neubias online school of image analysis

Neubias is back with new ideas! Neubias is the Network of European Bioimage Analysts and what they burn for is to help scientists analyze their images.

Possibly inspired by the Corona time, they will start an online school for image analysis based on video tutorials and online events.

Have a look at their new page called Neubias academy where they announce several events coming up in the next few months.

New image analysis training school with Neubias

NEUBIAS, the Network of European BioImage Analysts, is delighted to announce two new Training Schools on BioImage Analysis:

TS14 for Early Career Investigators (Life Scientists: PhD candidates, Postdocs, Staff, …):

This training school will cover the basics of image analysis using ImageJ/Fiji, as well as image analysis workflow automation using ImageJ macro programming. In addition, it will be taught how to use the software package ilastik for machine learning based image segmentation and object classification, and how to integrate ilastik into ImageJ macro based workflows. Moreover, an overview of further relevant bioimage analysis software packages will be given and there will be ample time for “Work on Your Own Data” sessions assisted by experienced Analysts.

TS15 for BioImage Analysts (advanced level):

This school targets bioimage analysts, who are willing to enhance their professional scope and techniques for improving the quality of their analysis, at the same time as willing to contribute with their knowledge and experience to the school. Prerequisite is a proficiency in at least one programming language (we do not train coding). The school focuses on workflow designing. This year, we will have a particular emphasis on statistics for bioimage analysis and related tools e.g. R and Python libraries. In addition, we will overview machine & deep learning components.

The schools will be held in Bordeaux, Feb 29 – Mar 03 2019, hosted at the Centre Broca Nouvelle-Aquitaine by the Bordeaux Imaging Center (BIC) and the Interdisciplinary Institute for Neuroscience. The selected students will be able to attend the whole NEUBIAS conference as part of the training.

NEUBIAS schools are an excellent opportunity to learn from many experts in Bioimage Analysis (we are expecting >20 specialists at the event) and “…a great mix of intensive learning and community networking” (former trainee testimonial). All schools include practical sessions “Work on Your Own Data”, plenary seminars and a session on ethics in image analysis.

Applications are now open (TS14 = 25 seats, TS15 = 35 seats and ~10+ trainers per school). Within the COST framework (funders of NEUBIAS), we will offer up to 7 travel grants per school to applicants who qualify.

Application deadline: December 12th 2019 Selection notification: December 20th 2019

More information about schools (programme & trainers) and venue, travel & lodge available at our website:

eubias.org/NEUBIAS/training-schools/

eubias.org/NEUBIAS/training-schools/eci/ts14-bordeaux-2020/

eubias.org/NEUBIAS/training-schools/analysts/ts15-bordeaux-2020/

We kindly ask that you help us reach out to all potential interested applicants.

on behalf of all NEUBIAS members, local organizers (Florian Levet and Fabrice Cordelières), scientific organizers (Romain Guiet, Elnaz Fazeli, Christian Tischer, Kota Miura, Marion Louveaux), and NEUBIAS Training Leaders Gabriel Martins and Fabrice Cordelières.

How to precisely measure the volume of a cell?

Measuring the volume of a cell is often done by labelling the cell membrane or its cytoplasm. Analysing large flat cells this way is easy but it is much harder for tiny cells like blood cells, yeast or bacteria.

Another way to measure volumes is to use a negative stain, i.e. where the medium is made fluorescent with a dye that does not go into the cell. The cell appears as a black hole in fluorescent images and unlike lipid-based membrane labelling, borders are even and easy to segment.

While many dyes can be used for live cells, one must choose large dyes when negatively imaging cells that have been fixed and permeabilized.

This paper and this one use high molecular weight (2000 KDa) Dextran to achieve these results and measure the size of bacteria.

This recent paper optimizes the technique.