Light-sheet microscopy · Molecular imaging

How do preclinical labs analyze, visualize, and process light-sheet microscopy data?

Cleared-tissue light-sheet fluorescence produces whole-organ three-dimensional datasets that can exceed a terabyte per study. You need to process those volumes: run automated feature extraction, visualize structures in 3D, quantify regions, and compare groups across a cohort.

What researchers typically do

Most preclinical neuroscience labs analyze light-sheet data in Fiji/ImageJ, Imaris, Aivia, MBF Bioscience platforms, or light-sheet instrument vendor software. Many of these tools, and their companion products or AI plugins, support semi-automated or manual segmentation, atlas alignment into standard atlas space, and regional quantification within the same ecosystem. That works well for individual datasets and exploratory analysis. At cohort scale, operator-dependent tracing introduces reproducibility variability and terabyte volumes strain workstation-based workflows. Aligning cleared-tissue light-sheet to a reference atlas does not recover native specimen geometry, either. Standard light-sheet workflows require removing tissue from the skull and chemically clearing it, steps that introduce deformations and shape changes. Registering the cleared volume into atlas standard space warps an already-deformed specimen to match a reference brain that was itself extracted from the skull and shaped by its own processing pipeline.

Anchor cleared-tissue light-sheet to in situ anatomic reference

With the NeuroSimplicity Molecular Imaging Module, you can process cleared-tissue light-sheet on institutional infrastructure through automated feature extraction, 3D visualization, quantitative analysis, and cohort comparison in deterministic, auditable pipelines. When you integrate the Anatomic Imaging Module, you can register light-sheet fluorescence to in situ micro-computed tomography (micro-CT) from the same specimen, preserving native geometry captured in the intact head before extraction and clearing introduced deformations. You can register reference atlases to the sample in native sample space (see the atlas registration guide) rather than warping the cleared volume into deformed standard atlas space. That lets you run real biodistribution studies and quantitative regional analysis in native sample space, with metrics you can compare across samples and groups in a cohort.

What the platform enables

  • Cleared-tissue processing with automated feature extraction, 3D visualization, and cohort comparison via the Molecular Imaging Module
  • Registration to in situ micro-CT from the same specimen via Anatomic Imaging Module integration
  • Biodistribution and quantitative regional analysis in native sample space, comparable across samples
  • Atlas registration to the sample (e.g., Allen Atlas CCFv3) in native sample space
  • Terabyte-scale batch processing on institutional infrastructure

More detail

The Molecular Imaging Module is one of the modules you select when licensing the Imaging Suite. The first module is included in the base platform license; each additional module is an add-on. See Next steps below for configuration and licensing.

For atlas registration to the sample, including population atlas generation across cohorts, see the atlas registration guide linked in Next steps.

To integrate light-sheet with micro-CT, whole-slide imaging, or spatial omics from the same specimen, see the multi-modal integration guide linked in Next steps.

Next steps

Atlas registration guideRegister Allen Atlas CCFv3 and other references to cleared-tissue volumes in native sample spaceConfigure Molecular Imaging ModulePlan module licensing and capacity for light-sheet cohort throughputMicro-CT analysis guideIn situ micro-CT that preserves native anatomy before clearing and light-sheet imagingMulti-modal integrationIntegrate light-sheet with micro-CT, whole-slide imaging, and spatial omics
Light-Sheet Microscopy Analysis & Visualization | NeuroSimplicity