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Signals Image Artist

Signals Image Artist is our next generation image analysis and management platform for high-content screening and cell imaging data. Quickly process, analyze, share, and store the vast volumes of data generated by high-content screening and cellular imaging, including 3D imaging, phenotypic screening, and cell painting – so you can get your answers sooner.​ Reduce time to results from days and weeks to hours!

The only commercially available platform that provides universal high-volume image data storage and analysis, Signals Image Artist supports image data from all major high-content screening and cellular imaging systems. It uses high performance computing and an industry standard object store to provide a scalable, multi-user solution for image analysis and management that can expand with your labs evolving needs.

Part Number INF02358
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Next Generation Image Analysis and Management

Signals Image Artist has powerful capabilities for processing, analyzing, storing, and sharing all your high-content screening and cell imaging data – so you can significantly cut your time to results.

  • Fast image data processing and image analysis even for complex assays powered by high performance computing
  • Easy-to-use assay building blocks with integrated Artificial Intelligence (AI) that make advanced image analysis straightforward
  • A central location to store all your image data with associated instrument metadata for an enduring picture of experiments
  • Compatible with all major high-content screening and cell imaging systems
  • Multi-user solution that can support your entire lab without compromising performance
  • Scalable data storage to expand with your labs needs over time
  • Seamless integration with PerkinElmer Opera Phenix® Plus and Operetta CLS high-content screening systems operated by Harmony® software, as well as Signals VitroVivo for profiling image data, hit selection, and more
  • Cloud and on-premise options

It is also part of our complete workflow solution for high-content screening that includes PhenoVue cellular imaging reagents, PhenoPlate imaging microplates, HCS instruments, software, and automation.

For All Your High-Content Screening and Cellular Imaging Data

High-content screening and cellular imaging experiments generate huge amounts of image data. With the latest applications such as phenotypic screening, cell painting, and 3D imaging which use more complex, physiologically-relevant disease models, the volume of data continues to grow.

To maximize all this valuable data, you need a powerful solution for image processing, management and storage, and for sharing data with colleagues.

Signals Image Artist allows you to bring together cell imaging data from a wide range of sources on a single software platform so that you can store, share, analyze, and re-analyze it seamlessly.

Image Analysis Designed for Biologists

Whether you are performing phenotypic screening, cell painting, 3D imaging, live cell imaging, or more routine assays, Signals Image Artist is designed to make it easy for biologists to perform sophisticated image analysis without any coding experience.

The software platform’s image analysis building blocks encapsulate many years of knowledge and expertise in cellular imaging and analysis - so that you can focus on the biology. By simply adding together building blocks such as “Find Nuclei” and “Calculate Cell Painting Properties”, users can quickly create image analysis protocols in just a few simple steps.

Built-in Artificial Intelligence (AI) and machine learning technologies allow users to train the software to develop image analysis algorithms. While other systems may require an image analysis expert to create an algorithm, Signals Image Artist uses proprietary machine-learning technology to make it easy for you to do it on your own. Using a learn-by-example approach, in just a few clicks segmented images can be classified quickly and easily.

This is all powered by high performance computing, so you can get your answers faster.

  • Get started without extensive training
  • Measure complex and subtle phenotypic responses
  • Compare multiple samples, plates, or batches to quality check your results
  • Kinetic measurement capabilities to track cells, reveal changes in cell properties, and provide information on cell movement
  • Use with Signals VitroVivo to perform screening data analysis and validation, QC analyses, calculate reliable normalization, multivariate hit stratification, dose response curves, and drug response profiling

Resources, Events & More
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Case Study

Phenotypic Characterization of Mitochondria in Breast Cancer Cells using Morphology and Texture Properties

This study illustrates the power of high content automated image analysis to quantify complex organelle morphologies, using the Opera system and the texture and STAR features of the Columbus system.


White Paper

Artificial Intelligence, Machine Learning and Deep Learning: Applications in Cellular Imaging for Improved Drug Discovery Productivity

There has been a lot of buzz around artificial intelligence, machine learning and deep learning. Is the reality living up to the hype?

In the world of cellular imaging and its application to drug discovery, there is evidence of real progress against some of the critical challenges facing scientists using these technologies.

In this white paper, you will learn about:

  • Challenges in cellular imaging and drug discovery that Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL) are helping to overcome
  • How these technologies are used by leading cellular imaging scientists
  • An outlook to how AI, ML and DL in cellular imaging have the potential to further advance drug discovery and improve productivity in the future

High Content Screening in Three Dimensions

Researchers are increasingly looking to 3D cell cultures, microtissues, and organoids to bridge the gap between 2D cell cultures and in vivo animal models. This whitepaper documents a streamlined procedure for getting the most information, as quickly as possible, using solutions from PerkinElmer.