Science Lab

Benvenuti nel portale delle conoscenze di Leica Microsystems. Troverete materiale didattico e di ricerca scientifica sul tema della microscopia. Il portale supporta i principianti, i professionisti esperti e gli scienziati nel loro lavoro quotidiano e negli esperimenti. Esplorate i tutorial interattivi e le note applicative, scoprite le basi della microscopia e le tecnologie di punta. Entrate a far parte della comunità di Science Lab e condividete la vostra esperienza.

Left-hand image: The distribution of immune cells (white) and blood vessels (pink) in white adipose tissue (image captured using the THUNDER Imager 3D Cell Culture). Right-hand image: The same image after automated analysis using Aivia, with each immune cell color-coded based on its distance to the nearest blood vessel. Image courtesy of Dr. Selina Keppler, Munich, Germany.

How to Remove Out-Of-Focus Blur and Improve Segmentation Accuracy

The specificity of fluorescence microscopy allows researchers to accurately observe and analyze biological processes and structures quickly and easily, even when using thick or large samples. However,…

The AI-Powered Pixel Classifier

Achieving reproducible results manually requires expertise and is tedious work. But now there is a way to overcome these challenges by speeding up this analysis to extract the real value of the image…

Using Machine Learning in Microscopy Image Analysis

Recent exciting advances in microscopy technologies have led to exponential growth in quality and quantity of image data captured in biomedical research. However, analyzing large and increasingly…

Applying AI and Machine Learning in Microscopy and Image Analysis

Prof. Emma Lundberg is a professor in cell biology proteomics at KTH Royal Institute of Technology, Sweden. She is also the director of the Cell Atlas, an integral part of the Swedish-based Human…

Separation of cells based on their tracking status: A colourised binary mask of a time-lapse microscopy field of view of medium confluency with individual cells highlighted as survivors if they can be tracked since the initial movie frame (cyan), incomers if they migrated into the field of view throughout the movie (yellow) or mistracks if an error occurred in the automated trajectory reconstruction (red).

Tracking Single Cells Using Deep Learning

AI-based solutions continue to gain ground in the field of microscopy. From automated object classification to virtual staining, machine and deep learning technologies are powering scientific…

Dynamic Signal Enhancement powered by Aivia: Truly simultaneous multicolor imaging of live cells (U2OS) in 3D

Artificial Intelligence and Confocal Microscopy – What You Need to Know

This list of frequently asked questions provides “hands-on” answers and is a supplement to the introductory article about Dynamic Signal Enhancement powered by Aivia "How Artificial Intelligence…

How Artificial Intelligence Enhances Confocal Imaging

In this article, we show how artificial intelligence (AI) can enhance your imaging experiments. Namely, how Dynamic Signal Enhancement powered by Aivia improves image quality while capturing the…

Fluorescence Lifetime-based Imaging Gallery

Confocal microscopy relies on the effective excitation of fluorescence probes and the efficient collection of photons emitted from the fluorescence process. One aspect of fluorescence is the emission…

Multicolor Image Gallery

Fluorescence multicolor microscopy, which is one aspect of multiplex imaging, allows for the observation and analysis of multiple elements within the same sample – each tagged with a different…