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Exploring Subcellular Spatial Phenotypes with SPARCS
Discover spatially resolved CRISPR screening (SPARCS), a platform for microscopy-based genetic screening for spatial subcellular phenotypes at the human genome scale.
Unlocking Insights in Complex and Dense Neuron Images Guided by AI
The latest advancement in Aivia AI image analysis software provides improved soma detection, additional flexibility in neuron tracing, 3D relational measurement including Sholl analysis and more.
What are the Challenges in Neuroscience Microscopy?
eBook outlining the visualization of the nervous system using different types of microscopy techniques and methods to address questions in neuroscience.
AI Microscopy Enables the Efficient Detection of Rare Events
Localization and selective imaging of rare events is key for the investigation of many processes in biological samples. Yet, due to time constraints and complexity, some experiments are not feasible…
Precise Spatial Proteomic Information in Tissues
Despite the availability of imaging-based and mass-spectrometry-based methods for spatial proteomics, a key challenge remains connecting images with single-cell-resolution protein abundance…
AI-Enabled Spatial Analysis of Complex 3D Datasets
VIDEO ON DEMAND - This edition of MicaCam offers practical advice on the extraction of publication grade insights from microscopy images. Our special guest Luciano Lucas (Leica Microsystems) will…
Fast, High Acuity Imaging and AI-assisted Analysis
The use of state-of-the-art AI systems is pushing image analysis into a new generation. Challenges like the conflict between imaging power and sample integrity are being overcome with THUNDER’s…
Create New Options for Live Cell Imaging
The use of state-of-the-art AI systems is pushing image analysis into a new generation. Challenges like the conflict between imaging power and sample integrity are being overcome with THUNDER’s…
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,…
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…
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,…
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…
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…
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…
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.
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…
Observing Complex Cellular Interactions at Multiple Scales
Learn how to observe challenging cellular interactions with easy to deploy object detection and relationship measurements.
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…
Save Time and Effort with AI-assisted Fluorescence Image Analysis
The powerful synergy of THUNDER and Aivia analyze fluorescence images with greater accuracy, even when using low light excitation.
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…
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…
AI in Microscopy Webinar
We demonstrate residual channel attention networks for restoring and enhancing volumetric time-lapse (4D) fluorescence microscopy data.
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