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Practical workshops: Unleash the value of microscopic data

Aivia workshops demonstrate the power of AI-based image analysis for various applications

Wetzlar, 21.09.2021 - In 4 sessions from September through November, the Aivia image analysis workshops will demonstrate how to extract deeper insights from 2D to 5D visualization data for cancer biology, neuroscience, cellular interactions, and developmental research.

Aivia allows biologists to use AI powered visualization and analysis to leverage the full capabilities of image data with no computer science expertise required. In the past, researchers had to master a wide array of tools to produce robust and reproducible results from complex data sets. Now Aivia has changed this. The state-of-the-art and innovative AI-powered image analysis software integrates effective tools powered by machine learning and deep learning technology for image segmentation, object classification, and novel-structure detection in a single platform.

Book your slot for the image analysis workshop by following the links below

  • Session 1: Simplifying Image Analysis Workflows for Cancer Biology | September 21 – 8am PT | 11 am ET | 5pm CEST
  • Session 2: Accelerating EM and Fluorescence Image Analysis of Neurons with Automation | October 12 – 8am PT | 11 am ET | 5pm CEST
  • Session 3: Observing Complex Cellular Interactions at Multiple Scales | November 2 – 8am PT | 11 am ET | 5pm CEST
  • Session 4: Examining Critical Developmental Events in High-Definition | November 30 – 8am PT | 11 am ET | 5pm CEST

Using an AI-based software architecture, Aivia image analysis software is a uniquely innovative and comprehensive platform for 2D-to-5D image visualization, analysis, and interpretation. It is designed for the reliable processing and reconstruction of highly complex images in just minutes.

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  • Session 2: Accelerating EM and Fluorescence Image Analysis of Neurons with Automation
  • Session 3: Observing Complex Cellular Interactions at Multiple Scales
  • Session 4: Examining Critical Developmental Events in High-Definition
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