Science Lab

Science Lab

Science Lab

The knowledge portal of Leica Microsystems offers scientific research and teaching material on the subjects of microscopy. The content is designed to support beginners, experienced practitioners and scientists alike in their everyday work and experiments. Explore interactive tutorials and application notes, discover the basics of microscopy as well as high-end technologies – become part of the Science Lab community and share your expertise!
Protist Paramecium (Paramecium tetraurelia) stained to show the nucleus

3D Spatial Analysis Using Mica's AI-Enabled Microscopy Software

This video offers practical advice on the extraction of publication grade insights from microscopy images. Our special guest Luciano Lucas (Leica Microsystems) will illustrate how Mica’s AI-enabled…
Image of fixed U2OS cell expressing mEmerald-Tomm20 denoised using a 3D RCAN model trained with matching low and high SNR image pairs acquired on an iSIM system.

AI Microscopy Image Analysis – An Introduction

Artificial intelligence-guided microscopy image analysis and visualization is a powerful tool for data-driven scientific discovery. AI can help researchers tackle challenging imaging applications,…
Dual color volume rendering of Drp1 oligomers (green) and mito OM (red) in a live U2OS cell

Multicolor 4D Super Resolution Light Sheet Microscopy

The AI Microscopy Symposium offers a unique forum for discussing the latest AI-based technologies and tools in the field of microscopy and biomedical imaging. In this scientific presentation, Yuxuan…
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…
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