Aivia
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Leica Microsystems
Aivia AI 이미지 분석 소프트웨어
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How to Streamline High-Plex Imaging for 3D Spatial Omics Advances
In this webinar, Dr. Julia Roberti and Dr. Luis Alvarez from Leica Microsystems introduce SpectraPlex, a new functionality integrated into the STELLARIS confocal platform for high-plex 3D spatial…
Boston and San Francisco Innovation Hubs
The Boston and San Francisco Innovation Hubs are here to help you advance scientific discovery. We provide academic and industrial researchers access to state-of-the-art microscope technology and…
Transforming Research with Spatial Proteomics Workflows
Spatial Proteomics, Nature Methods 2024 Method of the Year, is driving research advancements in cancer, immunology, and beyond. By combining positional data with high throughput imaging of proteins in…
Get to Insights Faster and Easier with AI Image Analysis Tools
Discover how Aivia helps scientists streamline image analysis with fast setup, accurate AI detection, and easy batch processing.
Unlocking the Secrets of Organoid Models in Biomedical Research
Get ready to delve deeper into the world of organoids and 3D models, which are essential tools for advancing our understanding of human health. Navigating these complex structures and obtaining clear…
Designing the Future with Novel and Scalable Stem Cell Culture
Visionary biotech start-up Uncommon Bio is tackling one of the world’s biggest health challenges: food sustainability. In this webinar, Stem Cell Scientist Samuel East shows how they make stem cell…
Explore Alzheimer's Spatial Proteome with Big Data
Alzheimer's disease, a genetic and sporadic neurodegenerative condition, leads to cognitive decline in mid to late life, marked by β-amyloid plaques and tau tangles. With limited treatment options,…
Uncover the Hidden Complexity of Colon Cancer with Big Data
Colorectal cancer poses a significant health burden. While surgery is effective initially, some patients develop recurrent secondary disease with poor prognosis, necessitating advanced therapies like…
Dive into Pancreatic Cancer Research with Big Data
Pancreatic cancer, with a mortality rate near 40%, is challenging to treat due to its proximity to major organs. This story explores the complex biology of pancreatic ductal adenocarcinoma (PDAC),…
Mapping Tumor Immune Landscape with AI-Powered Spatial Proteomics
Spatial mapping of untreated tumors provides an overview of the tumor immune architecture, useful for understanding therapeutic responses. Immunocompetent murine models are essential for identifying…
Deep Visual Proteomics Provides Precise Spatial Proteomic Information
Despite the availability of imaging methods and mass spectroscopy for spatial proteomics, a key challenge that remains is correlating images with single-cell resolution to protein-abundance…
Spatial Analysis of Neuroimmune Interactions in Alzheimer’s Disease
Alzheimer’s disease (AD) is a complex neurodegenerative disorder characterized by neurofibrillary tangles, β-amyloid plaques, and neuroinflammation. These dysfunctions trigger or are exacerbated by…
A Guide to Spatial Biology
What is spatial biology, and how can researchers leverage its tools to meet the growing demands of biological questions in the post-omics era? This article provides a brief overview of spatial biology…
Probing Human Alzheimer's Cortical Section using Spatial Multiplexing
Alzheimer’s disease (AD) is the most common neurodegenerative disease and is characterized by the progressive decline of cognitive function. Spatial profiling of AD brain may reveal cellular…
How Efficient is your 3D Organoid Imaging and Analysis Workflow?
Organoid models have transformed life science research but optimizing image analysis protocols remains a key challenge. This webinar explores a streamlined workflow for organoid research, starting…
How did Laser Microdissection enable Pioneering Neuroscience Research?
Dr. Marta Paterlini, a Senior Scientist at the Karolinska Institute, shares her experience of using laser microdissection (LMD) in groundbreaking research into adult human neurogenesis and offers…
AI-Powered Multiplexed Image Analysis to Explore Colon Adenocarcinoma
In this application note, we demonstrate a spatial biology workflow via an AI-powered multiplexed image analysis-based exploration of the tumor immune microenvironment in colon adenocarcinoma.
A Meta-cancer Analysis of the Tumor Spatial Microenvironment
Learn how clustering analysis of Cell DIVE datasets in Aivia can be used to understand tissue-specific and pan-cancer mechanisms of cancer progression
Mapping the Landscape of Colorectal Adenocarcinoma with Imaging and AI
Discover deep insights in colon adenocarcinoma and other immuno-oncology realms through the potent combination of multiplexed imaging of Cell DIVE and Aivia AI-based image analysis
Spatial Architecture of Tumor and Immune Cells in Tumor Tissues
Dig deep into the spatial biology of cancer progression and mouse immune-oncology in this poster, and learn how tumor metabolism can effect immune cell function.
Transforming Multiplexed 2D Data into Spatial Insights Guided by AI
Aivia 13 handles large 2D images and enables researchers to obtain deep insights into microenvironment surrounding their phenotypes with millions of detected objects and automatic clustering up to 30…
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…
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…
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…
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.
Fields of Application
세포생물학
인간의 건강과 질병을 기준으로 세포를 이해하는 것에 연구의 초점이 맞추어져 있다면 관심 세포를 시공간 및 분자 측면에서 자세히 조사하는 것은 매우 중요합니다. 이는 현미경이 세포생물학에서 매우 중요한 도구인 이유입니다. 현미경을 사용하면 세포 기관과 고분자를 분석할 뿐만 아니라, 시료의 구조적 환경 내에서 시료를 자세히 연구할 수 있습니다. 세포생물학…
