Unlock the Tools, Techniques, and Workflows Defining the Future of Spatial Biology


Spatial Imaging Demystified


Spatial Imaging is revolutionizing how we visualize biological processes. Advances in multiplexed imaging, digital microscopy, and high-resolution spatial assays are rapidly transforming how researchers interrogate tissue architecture, cellular neighborhoods, and complex disease microenvironments. Yet with an expanding array of platforms and chemistries, developing a robust spatial workflow can be challenging.

This comprehensive eBook—Spatial Imaging Demystified—guides researchers through the core principles, instrumentation, and experimental considerations needed to generate reproducible, high-content spatial datasets that preserve biological context and support translational discovery.


What You’ll Learn:

Foundational Concepts in Spatial Biology: Understand how spatial transcriptomics, proteomics, genomics, and metabolomics integrate digital imaging with molecular profiling to map biological processes within intact tissues.

Fundamentals of Spatial Imaging and Multiplex Fluorescence:  Explore the scientific basis of preserving spatial context—co-localization, segmentation, multiplexing, and tissue-level structural analysis—and how these principles elevate discovery in immuno-oncology, neuroscience, and pathology.

Technique Comparisons: Spectral vs. Cyclic Imaging: Gain clarity on when to deploy mid-plex spectral imaging versus high-plex cyclic methods, including tradeoffs in throughput, sample integrity, data quality, and panel design.

Designing Robust Spatial Imaging Experiments: Learn best practices in specimen preparation, antibody validation, image acquisition, cell segmentation, and cross-batch harmonization to ensure reproducible single-cell spatial data.

Mid-Plex Imaging and the Evolution of Practical Spatial Workflows

Discover why many labs are shifting toward 5–9 marker mid-plex imaging—balancing biological complexity with operational efficiency—and how the EVOS™ S1000 Spatial Imaging System supports streamlined, single-scan multiplex analysis.


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