Light-sheet · Molecular imaging

How do I analyze my light-sheet microscopy data?

Analyzing light-sheet data typically means 3D rendering, segmentation, regional quantification, and often aligning to the Allen Brain Atlas. NeuroSimplicity handles cleared-tissue volumes at terabyte scale — and uses sample-space atlas labeling so comparing to Allen CCFv3 does not warp your specimen.

When you analyze light-sheet data, keep the specimen in native space

If your light-sheet analysis pipeline ends with warping whole-organ volumes into Allen standard space, you risk deformation artifacts from clearing, mounting, and individual anatomy. NeuroSimplicity analyzes light-sheet fluorescence in native sample space, then maps Allen CCFv3 (or custom cohort atlases) onto your volume for regional counts, biodistribution, and cohort comparison — the atlas comes to your sample, not the other way around.

To analyze light-sheet microscopy data at scale, the Imaging Suite automates volumetric rendering, segmentation, and cross-modal registration with micro-CT or MRI — all within one on-premises platform.

When you need to align light-sheet data to the Allen Brain Atlas, NeuroSimplicity applies sample-space labeling: Allen CCFv3 regions are mapped onto your cleared-tissue volume so regional quantification reflects your specimen’s true geometry.

Whole-organ and cleared-tissue datasets support connectomics, vascular mapping, and biodistribution studies. The molecular imaging module is included in base licensing; pathology and spatial omics modules extend per-node capacity.

Key capabilities

  • Analyze light-sheet microscopy data at terabyte scale
  • Align light-sheet data to Allen CCFv3 via sample-space labeling
  • Automated volumetric rendering and segmentation
  • Cross-modal registration with micro-CT and MRI
  • Regional quantification and cohort comparison

Related resources

How to Analyze Light-Sheet Microscopy Data | NeuroSimplicity