Science Lab

Bem-vindo ao portal de conhecimento da Leica Microsystems. Você encontrará pesquisas científicas e material didático sobre o tema microscopia. O portal oferece suporte a iniciantes, profissionais experientes e cientistas em seus trabalhos e experimentos diários. Explore tutoriais interativos e notas de aplicação, descubra os fundamentos da microscopia, bem como as tecnologias de ponta. Faça parte da comunidade do Science Lab e compartilhe sua experiência.

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 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…

Analysis of anatomy and axon orientation of an adult mouse brain tissue with QLIPP.

Learning the Cellular Architecture from its Optical Properties

In the last 3 years, microscopists have started to use "AI based" solutions for a wide range of applications, including image acquisition optimization (smart microscopy), object classification, image…

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

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…