3D view of an segmented organoid.
Organoid analysis and visualization in 3D, courtesy of Dr. Martin Engel at Inventia Life Science. Organoid analysis and visualization in 3D, courtesy of Dr. Martin Engel at Inventia Life Science.
software

Advanced Image Analysis Made Easy with ZEISS arivis

High-Performance Insights from 2D to 4D for Research and Discovery

Image Analisis at New Levels of Ease

How ZEISS arivis simplifies your image analysis workflows

Unlike traditional image analysis solutions that struggle with large datasets or require specialized coding skills, the ZEISS arivis ecosystem handles the most demanding microscopy data on standard hardware. From individual researchers to enterprise labs, arivis scales to meet your needs while maintaining consistent performance and reproducibility. Review this webpage and read our user stories to learn why ZEISS arivis is used in applications from basic research to drug discovery, enabling trusted, reproducible results in 2D, 3D, and 4D analysis.

  • ​​AI-Powered Image Analysis

    Use AI models for standardized 3D assays, improved reproducibility, and automated quantification.​

  • Effortless Data Handling

    Work with large datasets from any imaging platform for comprehensive disease modeling.

  • Enhanced Cell Measurements

    Extract richer feature sets for Cell Painting and High-Content Analysis (HCA) assays.

  • Accelerated Research Timelines

    Scale assays from single images to thousands for faster translation to patient outcomes.

  • Seamless Colaboration

    Share data, assay workflows, and results across your team for better standardization.

  • No Coding Required

    Set up standardized assay workflows with a few clicks and avoid dependency on image specialists.

Discover Image Analysis Possibilities with ZEISS

Sample courtesy of Professor Guorui Huang Ph.D., Ruijin Hospital, Shanghai Jia Tong University School of Medicine.

AI for Image Analysis: Power Made Simple​

Train, customize, and deploy Deep Learning models - no coding required​

Unlock the potential of AI with ZEISS arivis. It offers both cloud infrastructure and local options, coupled with an intuitive AI model training interface, making customized Deep Learning accessible to all. Its human-centered model training simplifies the process, requiring minimal image annotations to initiate training. Once created, models deliver standardized, reproducible assay results that eliminate variability between experiments and researchers.​​

  • Accessible custom Deep Learning​
  • Instance (object-based) & semantic (pixel-based) segmentation​
  • Support for open-source models, such as Cellpose​
  • Support for diverse microscopy technologies and image formats​
  • DeepD3 for automated spine tracing in neuroscience research​
  • Improved standardization and reproducibility in 3D assays
  • Seamless integration and automation​
  • No need to code

With ZEISS arivis, we built the image analysis platform we always wished for – one that empowers researchers to customize, automate, and scale their workflows with AI.

Sreenivas Bhattiprolu, Ph.D.​ Head of Digital Solutions, ZEISS arivis
Heartbeat of zebrafish, nuclei tracked
Courtesy of Stone Elworthy and Emily Noël, data acquired at Wolfson Light Microscopy Facility, School of Biosciences at the University of Sheffield, UK.

Cell Biology: Quantify with Precision​

From single cells to comprehensive populations, extract meaningful data automatically​

Transform your cell biology research with ZEISS arivis's powerful quantification capabilities for complex cellular phenotypes. Easily segment, track, and analyze heterogeneous cell populations in complex microenvironments that better mimic in vivo conditions. Obtain reproducible measurements that capture subtle phenotypic changes without manual intervention. ​

  • Easily automated cell and nuclei counting with AI-based segmentation​
  • Cell or nuclei tracking across time series to analyze division and migration​
  • Confluency measurement for growth monitoring​
  • Phenotypic classification based on multiple parameters​ using AI or custom feature patterns​
  • Quantification of cell-cell relationships, such as distance measuerments and colocalization​
  • Batch processing for batch and high-content experiments

While the manual workflow enabled analyzing on an average 20 cells by an individual in a day, ZEISS arivis Cloud allowed several thousands.

Ravi Manjithaya, Ph.D.​ Head of Autophagy Lab, JNCASR​
Sample courtesy of InSphero AG. Schlieren, Switzerland

Organoid Research: Structural Analysis in 3D

From growth monitoring to detailed morphology analysis​

Advance your organoid research with ZEISS arivis's comprehensive 3D analysis capabilities, supporting the transition to reduced animal testing models. Automatically segment complex structures, quantify morphological changes, and analyze cellular organization within organoids in true 3D (not just maximum intensity projections). The software's ability to handle large volumetric datasets makes it ideal for lightsheet microscopy and other 3D imaging techniques essential for more efficient translation to human patient outcomes.​​

  • Automated organoid and lumen segmentation for volume quantification​
  • Cell and layer analysis within organoid structures​
  • Volume and feature analysis across time points to monitor development​
  • Robust analysis of different organoid types (intestinal, brain, kidney)​ and spheroids
  • Phenotypic classification based on custom feature patterns or AI
  • Compatibility with all major 3D imaging techniques​
  • True 3D analysis beyond maximum intensity projections for accurate morphology

Drug Discovery & High Content Analysis: Scale with Confidence

Process, analyze, and share large datasets efficiently​

Accelerate your drug discovery pipeline with ZEISS arivis's scalability for data-intensive applications. By centralizing data management and enabling parallel processing, the platform dramatically reduces time-to-results while maintaining consistency across 2D-4D assays. From individual analysis tasks to enterprise-wide deployments, ZEISS arivis adapts to support your complete drug discovery workflow with improved standardization for more reliable results and better regulatory compliance.​​

  • Centralized data management for multiple imaging systems and file formats​
  • Parallelized batch processing for thousands of images​
  • Flexible deployment options - on-premises, cloud (AWS), or hybrid​
  • Automated assay workflows with folder watching capabilities to trigger execution​
  • Optimized resource allocation to control computing costs​
  • Web-based access for seamless collaboration and result sharing
     

ZEISS arivis Hub gives us a unique integration of all the scientific imaging data from our microscopes. The platform allows us to manage data storage, access, and processing across our facility, freeing up valuable time of our scientists to concentrate on their research questions.

Prof. Marco Fritzsche, Ph.D. Scientific Director of the Oxford-ZEISS Centre of Excellence
Neurons in microscopy image traced and color marked

Neuroscience: Reveal Neural Complexity

From single neuron tracing to complete network analysis

Explore neural complexity with ZEISS arivis's powerful, automated tools designed specifically for neuroscience research. Trace and analyze complete neuron morphologies, and quantify dendritic spines - even in large, 3D datasets from cleared tissue or whole brain imaging. The software's advanced algorithms handle the intricate structures of the nervous system with precision, enabling discoveries that would be impossible with manual analysis. ​​

  • Automated 3D neuron tracing with state-of-the-art algorithms​
  • Dendritic spine detection based on state-of-the-art methods including or AI
  • Large 3D dataset handling for whole brain and cleared tissue
  • Volume fusion for combining several sub volumes​
  • Full integration into analysis workflows combining distance measurements and many more
  • Comprehensive morphological measurements of neuronal features

Using ZEISS arivis Cloud allows us to save hundreds of hours spent looking at neurons and manually counting their synapses. The reproducibility of the model application ensures that the data is comparable between different researchers on the team and hopefully, in the future, between different teams as well.

Urtė Neniškytė, Ph.D. Department of Neurobiology and Biophysics at Vilnius University

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