Leica Microsystems: Science Lab

Science Lab

Das Wissensportal von Leica Microsystems bietet Ihnen Wissens- und Lehrmaterial zu den Themen der Mikroskopie. Die Inhalte sind so konzipiert, dass sie Einsteiger, erfahrene Praktiker und Wissenschaftler gleichermaßen bei ihrem alltäglichen Vorgehen und Experimenten unterstützen. Entdecken Sie interaktive Tutorials und Anwendungsberichte, erfahren Sie mehr über die Grundlagen der Mikroskopie und High-End-Technologien - werden Sie Teil der Science Lab Community und teilen Sie Ihr Wissen!

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.

Accurately Analyze Fluorescent Widefield Images

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…

H&E stained micrograph of an intramucosal esophageal adenocarcinoma (left) enhanced with Aivia’s Pixel Classifier (right)

Simplifying the Cancer Biology Image Analysis Workflow

As cancer biology data sets grow, so do the challenges in microscopy image analysis. Aivia experts cover how to overcome these challenges with AI.

Single timepoint of a drosophilia embryo, 3D object detection

Examining Critical Developmental Events in High-Definition

Extended live cell imaging of embryo development requires a delicate balance between light exposure, temporal resolution and spatial resolution to maintain cells’ viability. Compromises between the…

Single timepoint of a time-lapse recording of mammary epithelial micro spheroid cultured in 3D highlighting individual mitotic events

Observing Complex Cellular Interactions at Multiple Scales

Learn how to observe challenging cellular interactions with easy to deploy object detection and relationship measurements.

Aivia_Neuroscience-VBE comparison mouse-1_traced_ROI

Accelerating Neuron Image Analysis with Automation

The ability to examine complex neural processes relies on the accurate reconstruction of neuronal networks at scale. Most data extraction methods in neuroscience research are time-consuming and…

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…