It’s always funny to see that the “old” maximum intensity projection is so used in picture reconstruction. Even if we all know artefacts created by this method, we often prefer a parameter free tool … In this article, a new way to do the 3D to 2D reduction is presented, the smooth manifold extraction, and it is compared to others one.

Three-dimensional fluorescence microscopy followed by image processing is routinely used to study biological objects at various scales such as cells and tissue. However, maximum intensity projection, the most broadly used rendering tool, extracts a discontinuous layer of voxels, obliviously creating important artifacts and possibly misleading interpretation. Here we propose smooth manifold extraction, an algorithm that produces a continuous focused 2D extraction from a 3D volume, hence preserving local spat

Source: Smooth 2D manifold extraction from 3D image stack | Nature Communications

Under the title of “High Content – Less Mess, More Mesh”, GEN (Genetic, Engeneering & Biotechnology news) has published this month an article about the advances that have made it possible to generate vaste datasets with decreasing costs and the need for comparing results and using informations collected from experiments on different cell types with different imaging systems.

“The biggest thing that needs to happen in the next few years is a more extensive interoperability of the information that is obtained from high-content screening and analysis,” insists Robert F. Murphy, Ph.D., the Ray and Stephanie Lane Professor of Computational Biology and professor of biological sciences, biomedical engineering, and machine learning at Carnegie Mellon University.

When descriptive features are used in the analysis of microscopy images, one of the challenges is to compare and integrate data across experiments, particularly when specific features captured using different experimental platforms may have different meanings for different investigators.

“One potential way to address this is to make the features interpretable,” suggests Dr. Murphy. “But that can be impossible if people use different microscopes, conditions, and objectives—and often different cells.”

Efforts to develop generative models of cellular organization and protein distribution from fluorescence microscopy images have been undertaken in Dr. Murphy’s laboratory. These efforts have led to the development of an open-source platform, the CellOrganizer project.

More details on GEN !

The first place has been won by Dr. Oscar Ruiz, of the University of Texas MD Anderson Cancer Center, for a confocal imaging of a 4 day-old zebrafish embryo.

4 day-old zebrafish

winner of the 2016 photomicrography competition

We invite you to spend your next break to explore these breathtaking images on the smallworld Nikon website. 🙂

We just begin a test period of the Operetta “High Content Imaging System” from Perkin Elmer. First impressions are very good, especially using confocal option for 3D imaging. As you can see below, neurites growth is quite easy to observe around and inside a spheroid of SH-SY5Y cells. To properly count it is more complicated for the moment but we progress in the mastering of “Harmony” and “Columbus” softwares, as for “Acapella” scripts. Our next challenge is to build comprehensive 3D visualisation with Volocity software.

It was a pleasure for us to welcome Antoine at HCS Pharma for a 6 week internship focused on statistics interpretation improvement. He worked particularly on cells culture homogeneity in a 96 wells plate, and effect of cells spatial localisation in a well on results interpretation. Now, after a well deserved holiday, he will prepare a M2 about “public statistics” in Rennes 1 university.

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